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CALIPSO HOMEUser’s Guide HOMEData Summaries → Lidar Level 2 Cloud, Aerosol and Merged Layer V4.20 Products

CALIPSO: Data User’s Guide - Data Product Descriptions - Lidar Level 2 Cloud, Aerosol, and Merged Layer V4.20 Products


Version 4.20 Level 2 Layer Products Description

The CALIPSO Cloud, Aerosol, and Merged Layer Products are built around two tightly coupled data types. The first of these is a set of column properties, which describe the temporal and spatial location of the vertical column (or, for averaged data, curtain) of atmosphere being sampled. Column properties include satellite position data and viewing geometry, information about the surface type and lighting conditions, and the number of features (e.g., cloud and/or aerosol layers) identified within the column. For each set of column properties, there is an associated set of layer properties. These layer properties specify the spatial and optical characteristics of each feature found, and include quantities such as layer base and top altitudes, integrated attenuated backscatter, layer-integrated volume depolarization ratio, and optical depth. Below we provide brief descriptions of each of the column properties and the layer properties. Where appropriate, we also provide an assessment of the quality and accuracy of the data in the current release.

The Cloud layer products only contain features classified as cloud reported at 1 km and 5 km spatial resolutions. Likewise, the Aerosol layer product only contains features classified as tropospheric aerosol and stratospheric aerosol, reported at 5 km spatial resolution. The Merged layer products contain features classified as cloud, tropospheric aerosol, and stratospheric aerosol, reported at 1/3 km and 5 km spatial resolution.

  • The 1/3 km merged layer products report cloud and aerosol detection information obtained at the highest spatial resolution of the lidar: 1/3 km horizontally and 30-m vertically. The maximum number of layers reported per profile is 5. Due to constraints on CALIPSO’s downlink bandwidth, this full resolution data is only available from ~8.3 km above mean sea level, down to -0.5 km below sea level.

  • The 1 km layer products report cloud detection information obtained at a horizontal resolution of 1 km, over a vertical range extending from ~20.2 km above mean sea level, down to -0.5 km below sea level. The maximum number of layers per profile reported is 10.

  • The 5 km layer products report cloud and aerosol detection information on a 5 km horizontal grid. The maximum number of layers reported per profile in the aerosol, cloud, and merged layer products are 8, 10, and 15, respectively.

    Users should be aware that while the 5 km layer products are reported on a uniform 5 km grid, the amount of horizontal averaging required to detect a layer may exceed 5 km. For example, detection of subvisible cirrus during daylight operations may require averaging to 20 km or even 80 km horizontally. In these cases, the layer properties of the feature detected are replicated as necessary to span the full extent of the averaging interval required for detection. For example, the layer properties for an aerosol layer that could only be detected after averaging over 20 km horizontally will be repeated over four consecutive 5 km columns.

The fundamental data product provided by the CALIPSO layer products is the vertical location of cloud and aerosol layer boundaries. All other layer properties -- e.g., integrated attenuated backscatters and layer two-way transmittances -- are computed with reference to these boundaries. To make proper use of the CALIPSO layer products, all users must be aware of the uncertainties inherent in the fully automated recognition of layer boundaries. Note too that clouds and aerosols are reported separately in the CALIPSO cloud and aerosol layer products. Therefore, to obtain a complete representation of all features detected within any region, users must use both the cloud and the aerosol layer products or use the merged layer product.

A Single_Shot_Detection VGroup is reported in the layer products which provides information at single shot (1/3 km) resolution for a subset of science datasets. The names of science data sets within this VGroup are prefixed with “ss”. Lidar surface retrieval information is reported within the Lidar_Surface_Detection VGroup. Note that the Single_Shot_Detection VGroup also contains a separate Lidar_Surface_Detection VGroup which reports surface retrieval information at single shot resolution.


Data Descriptions

In the text below we provide brief descriptions of individual data fields reported in the CALIPSO cloud and aerosol layer products. Where appropriate, we also provide an assessment of the quality and accuracy of the data in the current release. The data descriptions are grouped into several major categories, as follows:

Additionally all the science data sets (SDSs) are listed in the table to the right, click on the SDS name to go directly to the description.

Science Data Set (SDS) Product
Profile_ID All
Latitude All
Longitude All
Profile_Time All
Profile_UTC_Time All
Day_Night_Flag All
Off_Nadir_Angle All
Solar_Zenith_Angle All
Solar_Azimuth_Angle All
Scattering_Angle All
Spacecraft_Position All
Laser_Energy_532 1/3
Parallel_Column_Reflectance_532 All
Parallel_Column_Reflectance_Uncertainty_532 All
Parallel_Column_Reflectance_RMS_Variation_532 All
Perpendicular_Column_Reflectance_532 All
Perpendicular_Column_Reflectance_Uncertainty_532 All
Perpendicular_Column_Reflectance_RMS_Variation_532 All
Column_Integrated_Attenuated_Backscatter_532 All
Column_IAB_Cumulative_Probability All
Column_Optical_Depth_Cloud_532 5
Column_Optical_Depth_Cloud_Uncertainty_532 5
Column_Optical_Depth_Tropospheric_Aerosols_532 5
Column_Optical_Depth_Tropospheric_Aerosols_Uncertainty_532 5
Column_Optical_Depth_Stratospheric_Aerosols_532 5
Column_Optical_Depth_Stratospheric_Aerosols_Uncertainty_532 5
Column_Optical_Depth_Tropospheric_Aerosols_1064 5
Column_Optical_Depth_Tropospheric_Aerosols_Uncertainty_1064 5
Column_Optical_Depth_Stratospheric_Aerosols_1064 5
Column_Optical_Depth_Stratospheric_Aerosols_Uncertainty_1064 5
Column_Feature_Fraction 5
Tropopause_Height All
Tropopause_Temperature All
IGBP_Surface_Type All
Snow_Ice_Surface_Type All
Lidar_Surface_Elevation All
DEM_Surface_Elevation All
Minimum_Laser_Energy_532 1km cloud,5km cloud/aerosol/merged
Surface_Top_Altitude_532 All
Surface_Base_Altitude_532 All
Surface_Integrated_Attenuated_Backscatter_532 All
Surface_532_Integrated_Depolarization_Ratio All
Surface_532_Integrated_Attenuated_Color_Ratio All
Surface_Overlying_Integrated_Attenuated_Backscatter_532 All
Surface_Peak_Signal_532 All
Surface_Scaled_RMS_Background_532 All
Surface_Detection_Flags_532 All
Surface_Detection_Confidence_532 All
Surface_Detections_333m_532  
Surface_Detections_1km_532  
Surface_Top_Altitude_1064 All
Surface_Base_Altitude_1064 All
Surface_Integrated_Attenuated_Backscatter_1064 All
Surface_1064_Integrated_Depolarization_Ratio All
Surface_1064_Integrated_Attenuated_Color_Ratio All
Surface_Overlying_Integrated_Attenuated_Backscatter_1064 All
Surface_Peak_Signal_1064 All
Surface_Scaled_RMS_Background_1064 All
Surface_Detection_Flags_1064 All
Surface_Detection_Confidence_1064 All
Surface_Detections_333m_1064 5, 1
Surface_Detections_1km_1064 5
Normalization_Constant_Uncertainty 5
Calibration_Altitude_532 5
FeatureFinderQC 5
High_Resolution_Layers_Cleared 5
Number_Layers_Found All
Surface_Wind_Speed 5; Aerosol product only
Layer_Top_Altitude All
Layer_Base_Altitude All
Layer_Base_Extended All
Layer_Top_Pressure All
Midlayer_Pressure All
Layer_Base_Pressure All
Layer_Top_Temperature All
Layer_Centroid_Temperature Cloud & Merged
Midlayer_Temperature All
Layer_Base_Temperature All
Opacity_Flag 5
Horizontal_Averaging 5
Attenuated_Scattering_Ratio_Statistics_532 All
Attenuated_Backscatter_Statistics_532 All
Integrated_Attenuated_Backscatter_532 All
Integrated_Attenuated_Backscatter_Uncertainty_532 All
Attenuated_Backscatter_Statistics_1064 All
Integrated_Attenuated_Backscatter_1064 All
Integrated_Attenuated_Backscatter_Uncertainty_1064 All
Volume_Depolarization_Ratio_Statistics All
Integrated_Volume_Depolarization_Ratio All
Integrated_Volume_Depolarization_Ratio_Uncertainty All
Attenuated_Total_Color_Ratio_Statistics All
Integrated_Attenuated_Total_Color_Ratio All
Integrated_Attenuated_Total_Color_Ratio_Uncertainty All
Overlying_Integrated_Attenuated_Backscatter_532 All
Layer_IAB_QA_Factor All
Feature_Classification_Flags All
Layer_Type Merged
ExtinctionQC_532 5
ExtinctionQC_1064 5; Aerosol product only
CAD_Score All
Initial_CAD_Score 5, Cloud product only
Measured_Two_Way_Transmittance_532 5
Measured_Two_Way_Transmittance_Uncertainty_532 5
Two_Way_Transmittance_Measurement_Region 5
Feature_Optical_Depth_532 5
Feature_Optical_Depth_Uncertainty_532 5
Initial_532_Lidar_Ratio 5
Final_532_Lidar_Ratio 5
Final_532_Lidar_Ratio_Uncertainty 5
Lidar_Ratio_532_Selection_Method 5
Layer_Effective_532_Multiple_Scattering_Factor 5
Integrated_Particulate_Depolarization_Ratio 5
Integrated_Particulate_Depolarization_Ratio_Uncertainty 5
Particulate_Depolarization_Ratio_Statistics 5
Feature_Optical_Depth_1064 5; Aerosol product only
Feature_Optical_Depth_Uncertainty_1064 5; Aerosol product only
Initial_1064_Lidar_Ratio 5; Aerosol product only
Final_1064_Lidar_Ratio 5; Aerosol product only
Final_1064_Lidar_Ratio_Uncertainty 5; Aerosol product only
Lidar_Ratio_1064_Selection_Method 5; Aerosol product only
Layer_Effective_1064_Multiple_Scattering_Factor 5; aerosol products only
Integrated_Particulate_Color_Ratio 5
Integrated_Particulate_Color_Ratio_Uncertainty 5
Particulate_Color_Ratio_Statistics 5
Ice_Water_Path 5; Cloud product only
Ice_Water_Path_Uncertainty 5; Cloud product only
Relative_Humidity 5; Aerosol product only
Single_Shot_Cloud_Cleared_Fraction 5
ssProfile_ID 5
ssLatitude 5
ssLongitude 5
ssProfile_Time 5
ssProfile_UTC_Time 5
ssParallel_Column_Reflectance_532 5
ssParallel_Column_Reflectance_Uncertainty_532 5
ssPerpendicular_Column_Reflectance_532 5
ssPerpendicular_Column_Reflectance_Uncertainty_532 5
ssColumn_Integrated_Attenuated_Backscatter_532 5
ssColumn_IAB_Cumulative_Probability 5
ssDEM_Surface_Elevation 5
ssLaser_Energy_532 5
ssNumber_Layers_Found 5
ssLayer_Top_Altitude 5
ssLayer_Base_Altitude 5
ssLayer_Top_Pressure 5
ssMidlayer_Pressure 5
ssLayer_Base_Pressure 5
ssLayer_Top_Temperature 5
ssLayer_Centroid_Temperature 5
ssMidlayer_Temperature 5
ssLayer_Base_Temperature 5
ssOpacity_Flag 5
ssAttenuated_Scattering_Ratio_Statistics_532 5
ssAttenuated_Backscatter_Statistics_532 5
ssIntegrated_Attenuated_Backscatter_532 5
ssIntegrated_Attenuated_Backscatter_Uncertainty_532 5
ssAttenuated_Backscatter_Statistics_1064 5
ssIntegrated_Attenuated_Backscatter_1064 5
ssIntegrated_Attenuated_Backscatter_Uncertainty_1064 5
ssVolume_Depolarization_Ratio_Statistics 5
ssIntegrated_Volume_Depolarization_Ratio 5
ssIntegrated_Volume_Depolarization_Ratio_Uncertainty 5
ssAttenuated_Total_Color_Ratio_Statistics 5
ssIntegrated_Attenuated_Total_Color_Ratio 5
ssIntegrated_Attenuated_Total_Color_Ratio_Uncertainty 5
ssOverlying_Integrated_Attenuated_Backscatter_532 5
ssLayer_IAB_QA_Factor 5
ssCAD_Score 5
ssInitial_CAD_Score 5, excluding 5km aerosol
ssFeature_Classification_Flags 5
ssWas_Cleared 5, 1/3
ssSurface_Top_Altitude_532 5
ssSurface_Base_Altitude_532 5
ssSurface_Integrated_Attenuated_Backscatter_532 5
ssSurface_532_Integrated_Depolarization_Ratio 5
ssSurface_532_Integrated_Attenuated_Color_Ratio 5
ssSurface_Overlying_Integrated_Attenuated_Backscatter_532 5
ssSurface_Peak_Signal_532 5
ssSurface_Scaled_RMS_Background_532 5
ssSurface_Detection_Flags_532 5
ssSurface_Detection_Confidence_532 5
ssSurface_Top_Altitude_1064 5
ssSurface_Base_Altitude_1064 5
ssSurface_Integrated_Attenuated_Backscatter_1064 5
ssSurface_1064_Integrated_Depolarization_Ratio 5
ssSurface_1064_Integrated_Attenuated_Color_Ratio 5
ssSurface_Overlying_Integrated_Attenuated_Backscatter_1064 5
ssSurface_Peak_Signal_1064 5
ssSurface_Scaled_RMS_Background_1064 5
ssSurface_Detection_Flags_1064 5
ssSurface_Detection_Confidence_1064 5

Column Time Parameters

Day_Night_Flag
This field indicates the lighting conditions at an altitude of ~24 km above mean sea level; 0 = day, 1 = night.

Profile_Time
Time expressed in International Atomic Time (TAI). Units are in seconds, starting from January 1, 1993. Times reported in the 1/3 km layer products are for the individual laser pulses from which the layer statistics were derived. Times reported in the 1 km layer products represent the temporal midpoint of the three laser pulses averaged to generate the 1 km horizontal resolution. For the 5 km layer products, three values are reported: the time for the first pulse included in the 15 shot average; the time for the final pulse; and the time at the temporal midpoint (i.e., at the 8th of 15 consecutive laser shots). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Profile_UTC_Time
Time expressed in Coordinated Universal Time (UTC), and formatted as 'yymmdd.ffffffff', where 'yy' represents the last two digits of year, 'mm' and 'dd' represent month and day, respectively, and 'ffffffff' is the fractional part of the day. Times reported in the 1/3 km layer products are for the individual laser pulses from which the layer statistics were derived. Times reported in the 1 km layer products represent the temporal midpoint of the three laser pulses averaged to generate the 1 km horizontal resolution. For the 5 km layer products, three values are reported: the time for the first pulse included in the 15 shot average; the footprint latitude at the temporal midpoint; and the the footprint latitude for the final pulse respectively (i.e., at the 8th of 15 consecutive laser shots). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Column Geolocation Information

Latitude
Geodetic latitude, in degrees, of the laser footprint on the Earth’s surface. Latitudes reported in the 1/3 km layer products are for the individual laser pulses from which the layer statistics were derived. The latitudes reported in the 1 km layer products represent footprint latitude at the temporal midpoint of the three laser pulses averaged to generate the 1 km horizontal resolution. For the 5 km layer products, three values are reported: the footprint latitude for the first pulse included in the 15 shot average; the footprint latitude at the temporal midpoint; and the footprint latitude for the final pulse respectively (i.e., at the 8th of 15 consecutive laser shots). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Longitude
Longitude, in degrees, of the laser footprint on the Earth's surface. Longitudes reported in the 1/3 km layer products are for the individual laser pulses from which the layer statistics were derived. The longitudes reported in the 1 km layer products represent footprint longitude at the temporal midpoint of the three laser pulses averaged to generate the 1 km horizontal resolution. For the 5 km layer products, three values are reported: the footprint longitude for the first pulse included in the 15 shot average; the footprint longitude at the temporal midpoint; and the footprint longitude for final pulse respectively (i.e., at the 8th of 15 consecutive laser shots). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Profile_ID
A unique identifier for each profile. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Column Spacecraft Orientation

Off_Nadir_Angle
The angle, in degrees, between the viewing vector of the lidar and the nadir angle of the spacecraft. Beginning in June 2006, CALIPSO operated with the lidar pointed at 0.3 degrees off-nadir (along track in the forward direction), with the exception of November 6-17, 2006 and August 21 to September 7, 2007. During these periods, CALIPSO operated with the lidar pointed at 3.0 degrees off nadir. Beginning November 28, 2007, the off-nadir angle was permanently changed to 3.0 degrees.

Scattering_Angle
The angle, in degrees, between the lidar viewing vector and the line of sight to the sun.

Solar_Azimuth_Angle
The azimuth angle, in degrees, from north of the line of sight to the sun.

Solar_Zenith_Angle
The angle, in degrees, between the zenith at the lidar footprint on the surface and the line of sight to the sun.

Spacecraft_Position
Reports the position, in kilometers, of the CALIPSO satellite. The position is expressed in Earth Centered Rotating (ECR) coordinate system as X-axis in the equatorial plane through the Greenwich meridian, the Y-axis lies in the equatorial plane 90 degrees to the east of the X-axis, and the Z-axis is toward the North Pole.

Laser_Energy_532
This field reports the minimum 532 nm laser energy, in Joules, contained within each horizontal 80 km segment (the coarsest resolution, see the layer detection ATBD) used by the feature detection algorithm.

Column Surface Properties


DEM_Surface_Elevation (external)
Surface elevation at the lidar footprint, in kilometers above local mean sea level, obtained from the GTOPO30 digital elevation map (DEM). The 5 km layer products report the minimum, maximum, mean, and standard deviation of all DEM surface samples along the 5 km averaging interval.

Minimum_Laser_Energy_532
This field reports the minimum 532 nm laser pulse energy, in Joules, within each 80 km along-track data segment (80 km = 240 laser pulses). The 80 km distance matches the largest horizontal extent considered in CALIOP’s standard level 2 data analyses. Since layers can be detected at horizontal resolutions as large as 80 km, anomalously low laser energies in coarse resolution upper layers can potentially introduce biases in the spatial and optical property retrievals of underlying layers detected at finer spatial resolutions. The Minimum_Laser_Energy_532 SDS enables ready identification of these problematic situations. See the Data Advisory web page for information on the occurrence of anomalously low laser energy shots, their impact on data quality, and for specific guidance on how to use Minimum_Laser_Energy_532 to identify affected profiles.

IGBP_Surface_Type (external)
International Geosphere/Biosphere Programme (IGBP) classification of the surface type at the lidar footprint. The IGBP surface types reported by CALIPSO are the same as those used in the CERES/SARB surface map. The CERES/SARB surface map table is below.

CERES/SARB Surface Map
Surface Index Surface Type   Surface Index Surface Type
1 Evergreen-Needleleaf-Forest   10 Grassland
2 Evergreen-Broadleaf-Forest   11 Wetland
3 Deciduous-Needleleaf-Forest   12 Cropland
4 Deciduous-Broadleaf-Forest   13 Urban
5 Mixed-Forest   14 Crop-Mosaic
6 Closed-Shrublands   15 Permanent-Snow
7 Open-Shrubland (Desert)   16 Barren/Desert
8 Woody-Savanna   17 Water
9 Savanna   18 Tundra

Snow_Ice_Surface_Type (external)
Snow and ice coverage for the surface at the lidar footprint; data obtained from the National Snow and Ice Data Center (NSIDC).

Surface_Top_Altitude_532
Surface_Top_Altitude_1064
Top altitude of the surface return in the 532 nm and 1064 nm channels at the lidar footprint in kilometers above local mean sea level. Contains fill values when surface is not detected. Surface top altitudes are not guaranteed to agree in both channels due to the difference in averaging resolutions at the surface (30 m vs. 60 m at 532 nm and 1064 nm, respectively). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Base_Altitude_532
Surface_Base_Altitude_1064
Base altitude of the surface return in the 532 nm and 1064 nm channels at the lidar footprint in kilometers above local mean sea level. Contains fill values when surface is not detected. Surface base altitude are not guaranteed to agree in both channels due to the difference in averaging resolutions at the surface (30 m vs. 60 m at 532 nm and 1064 nm, respectively) and also due to the non-ideal detector response in the 532 nm channels which may yield base altitudes much below that of the 1064 nm channel. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Integrated_Attenuated_Backscatter_532
Vertically integrated Total Attenuated Backscatter 532 nm of the surface return from Surface Top Altitude 532 to Surface Base Altitude 532. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Integrated_Attenuated_Backscatter_1064
Vertically integrated Attenuated Backscatter 1064 nm of the surface return from Surface Top Altitude 1064 to Surface Base Altitude 1064. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_532_Integrated_Depolarization_Ratio
Depolarization ratio of surface return at 532 nm from Surface Top Altitude 532 to Surface Base Altitude 532, computed as the ratio of vertically integrated Perpendicular Attenuated Backscatter 532 to vertically integrated parallel attenuated backscatter 532 nm. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_1064_Integrated_Depolarization_Ratio
Depolarization ratio of surface return at 532 nm from Surface Top Altitude 1064 to Surface Base Altitude 1064, computed as the ratio of vertically integrated Perpendicular Attenuated Backscatter 532 to vertically integrated parallel attenuated backscatter 532 nm. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_532_Integrated_Attenuated_Color_Ratio
Attenuated color ratio of surface return from Surface Top Altitude 532 to Surface Base Altitude 532, computed as the ratio of vertically integrated Attenuated Backscatter 1064 to vertically integrated Total Attenuated Backscatter 532. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_1064_Integrated_Attenuated_Color_Ratio
Attenuated color ratio of surface return from Surface Top Altitude 1064 to Surface Base Altitude 1064, computed as the ratio of vertically integrated Attenuated Backscatter 1064 to vertically integrated Total Attenuated Backscatter 532. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Overlying_Integrated_Attenuated_Backscatter_532
Vertically integrated Total Attenuated Backscatter 532 from 40 km to one range bin above Surface Top Altitude 532. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Overlying_Integrated_Attenuated_Backscatter_1064
Vertically integrated Attenuated Backscatter 1064 from 40 km to one range bin above Surface Top Altitude 1064. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Detection_Flags_532
Surface_Detection_Flags_1064
Bit-mapped 16-bit integers describing the success of surface detection within the indicated channel, the surface detection method, information about saturated surfaces or surfaces affected by the negative signal anomaly, and diagnostic failure information. Bits are interpreted as follows:
Bit(s) Interpretation
1 Surface detected (0 = no, 1 = yes)
2-3 Surface detection method; values interpreted as follows
0 = derivative test
1 = multi-shot averaged data test
2 = single shot surface detection fraction test
3 = unused
4-6 Is saturated; 532 parallel, 532 perpendicular and 1064, respectively
7-9 Has negative signal anomaly; 532 parallel, 532 perpendicular and 1064, respectively
10 Derivative method failure: Z(min gradient) < Z(max gradient)
11 Derivative method failure: vertical extent exceeds limit
12 Derivative method failure: peak signal below threshold
13 Failure: vertical separation between 532 and 1064 surface top altitudes exceeds allowable limit
14 Failure: surface detected at 1064 nm only, but overlying color ratio below threshold
15-16 Unused

Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.


Surface_Detection_Confidence_532
Surface_Detection_Confidence_1064
Not implemented in this release. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Scaled_RMS_Background_532
Surface_Scaled_RMS_Background_1064
Background noise estimate computed from RMS baseline noise measurements between 65 and 80 km AMSL, rescaled to create a pseudo attenuated backscatter coefficient with units of per kilometer per steradian. The version 4 surface detection algorithm requires the surface signal to exceed the scaled RMS background noise estimate by a multiplicative constant. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Peak_Signal_532
Surface_Peak_Signal_1064
Maximum attenuated backscatter value of the surface signal within the indicated channel. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Surface_Detections_333m_532 (1 km and 5 km products only)
Surface_Detections_333m_1064 (1 km and 5 km products only)
Number of single shot profiles (1/3 km resolution) within each 5 km or 1 km resolution profile where surface was detected on the indicated channel.

Surface_Detections_1km_532 (5 km products only)
Surface_Detections_1km_1064 (5 km products only)
Number of 1 km resolution profiles within each 5 km resolution profile where surface was detected in the indicated channel.

Column Meteorological Data


Surface_Wind_Speed (aerosol products only)
Zonal and meridional surface wind speeds, in meters per second, obtained from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System.

Tropopause_Height (external)
Tropopause height, in kilometers above local mean sea level; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System.

Tropopause_Temperature (external)
Tropopause temperature, in degrees C; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System.

Column Optical Properties


Column_Feature_Fraction (5 km products only)
The fraction of the 5-km horizontally averaged profile, between 30-km and the DEM surface elevation, which has been identified as containing a feature (i.e., either a cloud, an aerosol, or a stratospheric layer)

Column_Integrated_Attenuated Backscatter_532 (5 km products only)
The integral with respect to altitude of the 532 nm total attenuated backscatter coefficients. The limits of integration are from the onset of the backscatter signal at ~40 km, down to the range bin immediately prior to the surface elevation specified by the digital elevation map. This quantity represents the total attenuated backscatter measured within a column. Physically meaningful values of the column integrated attenuated backscatter (hereafter, γ′column) range from ~0.01 sr (completely clear air), to greater than 1.5 sr (e.g., due to anomalous backscatter from horizontally oriented ice crystals; see Hu et al. (Optics Express 15, 2007)). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Column_IAB_Cumulative_Probability (5 km products only)
The cumulative probability of measuring a total column integrated attenuated backscatter value equal to the value computed for the current profile. Values in this field range between 0 and 1. The cumulative probability distribution function, shown below in Figure 1, was compiled using all CALIOP total column IAB measurements acquired between 15 June, 2006 and 18 October, 2006. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Figure 1: Distribution of γ′column at 532 nm
Column IAB distribution at 532 nm.

Column_Optical_Depth_Cloud_532 (5 km products only)
Optical depth of all clouds detected within a 5 km averaged profile, obtained by integrating the 532 nm cloud extinction profile reported in the CALIPSO 5 km Cloud Profile Products.

Column_Optical_Depth_Cloud_Uncertainty_532 (5 km products only)
Estimated uncertainty in the Column Optical Depth Cloud 532 parameter, computed according to the CALIPSO Version 3 Extinction Uncertainty Document (PDF).

Column_Optical_Depth_Tropospheric_Aerosols_532 (5 km products only)
Optical depth of all tropospheric aerosols detected within a 5 km averaged profile, obtained by integrating the 532 nm aerosol extinction profile reported in the CALIPSO 5 km Aerosol Profile Products.

Column_Optical_Depth_Tropospheric_Aerosols_Uncertainty_532 (5 km products only)
Estimated uncertainty in the Column Optical Depth Tropospheric Aerosol 532 parameter, computed according to the CALIPSO Version 3 Extinction Uncertainty Document (PDF).

Column_Optical_Depth_Tropospheric_Aerosols_1064 (5 km products only)
Optical depth of all tropospheric aerosols detected within a 5 km averaged profile, obtained by integrating the 1064 nm aerosol extinction profile reported in the CALIPSO 5 km Aerosol Profile Products.

Column_Optical_Depth_Tropospheric_Aerosols_Uncertainty_1064 (provisional; 5-km products only)
Estimated uncertainty in the Column Optical Depth Tropospheric Aerosol 1064 parameter, computed according to the CALIPSO Version 3 Extinction Uncertainty Document (PDF).

Column_Optical_Depth_Stratospheric_Aerosols_532 (5 km products only)
Optical depth of all stratospheric aerosols within a 5 km averaged profile, obtained by integrating the stratospheric particulate extinction coefficients reported at 532 nm in the CALIPSO 5 km Aerosol Profile Products.

Column_Optical_Depth_Stratospheric_Aerosols_Uncertainty_532 (5 km products only)
Estimated uncertainty in the Column Optical Depth Stratospheric Aerosols 532 parameter, according to the CALIPSO Version 3 Extinction Uncertainty Document (PDF).

Column_Optical_Depth_Stratospheric_Aerosols_1064 (5 km products only)
Optical depth of all stratospheric aerosols within a 5 km averaged profile, obtained by integrating the stratospheric particulate extinction coefficients reported at 1064 nm in the CALIPSO 5 km Aerosol Profile Products.

Column_Optical_Depth_Stratospheric_Aerosols_Uncertainty_1064 (5 km products only)
Estimated uncertainty in the Column Optical Depth Stratospheric 1064 parameter, according to the CALIPSO Version 3 Extinction Uncertainty Document (PDF).

Parallel_Column_Reflectance_532
Bi-directional column reflectance derived from the root-mean-square (RMS) variation of the 532 nm parallel channel background measurements. For the 1/3 km layer products, single shot values are reported; for the 1 km and 5 km layer products, mean values are reported. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Parallel_Column_Reflectance_RMS_Variation_532 (provisional; 5-km products only)
The RMS variation of the parallel channel reflectance values computed using the 15 samples that comprise a nominal 5-km horizontal swath of CALIOP lidar measurements.

Parallel_Column_Reflectance_Uncertainty_532
Not calculated for the current release; data products contain fill values in this field. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Perpendicular_Column_Reflectance_532
Bi-directional column reflectance derived from the RMS variation of the 532 nm perpendicular channel background measurements. For the 1/3 km layer products, single shot values are reported; for the 1 km and 5 km layer products, mean values are reported.

Perpendicular_Column_Reflectance_RMS_Variation_532 (5 km products only)
The RMS variation of the perpendicular channel reflectance values computed using the 15 samples that comprise a nominal 5-km horizontal swath of CALIOP lidar measurements.

Perpendicular_Column_Reflectance_Uncertainty_532
Not calculated for the current release; data products contain fill values in this field. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Column QA Information

Calibration_Altitude_532 (external)
Top and base altitudes, in kilometers above mean sea level, of the region of the atmosphere used for calibrating the 532 nm parallel channel. The calibration algorithm and procedures are explained in detail in the CALIOP Level 1 ATBD (PDF).

Feature_Finder_QC
To generate data at a nominal 5 km horizontal resolution requires averaging 15 consecutive laser pulses. For each 5 km average, we report a set of feature finder QC flags. Conceptually, these flags are a set of 15 Boolean values which tell the user whether or not a feature (cloud, aerosol, or surface echo) was detected in each of the 15 laser pulses. The flags are implemented as a 16-bit integer. The most significant bit is unused, and always set to zero. Each of the 15 remaining bits represents the "features found" state for a single full-resolution profile. A bit value of zero indicates that one or more features were found within the profile. A feature finder QC flag value of zero for any 5 km column indicates complete feature finder success.

Normalization_Constant_Uncertainty (provisional)
Uncertainty in the 532 nm and 1064 nm calibration constants due solely to random error in the backscatter measurements in the calibration region; reported as a relative error (i.e., dC/C) in a N x 2 array, with the 532 nm uncertainties stored in first column, and the 1064 nm uncertainties in the second column.

Layer Spatial Properties


Horizontal_Averaging (5 km products only)
The amount of horizontal averaging required for a feature to be detected. For all data versions up to and including the 3.01 release, the values in this field will be either 0, 5, 20, or 80. 0 is a fill value; the remaining values indicate features detected at 5-km, 20-km, and 80-km averaging intervals, respectively.

Layer_Top_Altitude and Layer_Base_Altitude
Layer top and base altitudes are reported in units of kilometers above mean sea level. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution. Due to the on-board data averaging scheme, the precision with which CALIPSO can make this measurement is itself a function of altitude. Between -0.5 km and ~8.2 km, the vertical resolution of the lidar is 30-meters. From ~8.2 km to ~20.2 km, the vertical resolution of the lidar is 60-meters. Above ~20.2 km, the vertical resolution is 180-meters.

The CALIOP layer detection algorithm used for the Version 1 and Version 2 data releases is described in detail in Vaughan et al., 2009 and in the CALIPSO Feature Detection ATBD (PDF). For Version 3 and later versions, an additional refinement has been incorporated into the base determination procedure. Under certain conditions, described here, the initial estimate of base altitude for those layers identified as aerosols will be extended to a new, lower altitude located 90 m above the local surface. The Layer Base Extended flag identifies those layers for which the base altitude has been altered by this procedure.

The uncertainties associated with detection of cloud and aerosol layers in backscatter lidar data are examined in detail in Section 5 of the CALIPSO Feature Detection ATBD (PDF). The ATBD contains quantitative assessments of feature finder performance derived using simulated data sets, for which all layer boundaries were known exactly. In the real world of layer detection, we do not have access to this underlying truth. Therefore in this document we provide the following set of "rules of thumb" that users can apply to the data products to obtain a qualitative understanding of the layer boundaries reported, and of the optical properties associated with these layers.

  1. Strongly scattering features are easier to detect than weakly scattering features. The scattering intensity of each layer is reported in the 532 nm and 1064 nm attenuated backscatter statistics and by the integrated attenuated backscatter at 532 nm and 1064 nm.

  2. Detection of layers during the nighttime portion of the orbits is more reliable than during the daytime portion of the orbits. Due to solar background signals, the noise levels in the daytime measurements are much larger than those at night, and this additional noise can obscure faint features, and can lead to boundary detection errors even in more strongly scattering layers.

  3. Features become increasingly difficult to detect with increasing optical depth above feature top. Put another way, detection of the lower layers in a multi-layer scene is made more difficult by the signal losses that occur as the laser light passes through the upper layers. (In a sense, this is a restatement of (a), since the backscatter intensity of secondary features is reduced from what it otherwise might be by the signal attenuation caused by the overlying features.) The Overlying Integrated Attenuated Backscatter and the Layer Integrated Attenuated Backscatter QA factor serve as proxies for the optical depth above each feature, and thus provide qualitative assessments of the confidence that users should assign to the reported layer properties.

  4. In general, our confidence in the location of the top of a layer is somewhat greater than our confidence in the location of the base of the same layer. For transmissive features, one reason for this is that the backscatter signal is attenuated by traversing the feature, thus degrading the potential contrast between feature and "non-feature" at the base. Additionally, in strongly scattering layers, multiple scattering effects and signal perturbations introduced by the non-ideal transient response of the 532 nm detectors can also make base determination less certain.

  5. The Opacity Flag is used to indicate features that completely attenuate the backscatter signal. For these features, the base altitude reported must be considered as an "apparent" base rather than a true base.

  6. In those cases where the layer base has been extended to 90 m above the local surface, the assumption is that extended region contains aerosol that lies below the detection limits of the standard algorithm. The resulting increase in aerosol optical depths indicates that this procedure is appropriate far more often than not.

  7. Stratospheric features reported during daylight -- especially those reported above 20 km between 60N and 60S -- are often noise artifacts and should be treated with suspicion.

Additional assessments of layer detection performance can be found in McGill et al., 2007 and Vaughan et al., 2009

Number_Layers_Found
The number of layers found in this column; cloud layer products report (only) the number of cloud layers found, aerosol layer products report (only) the number of aerosol layers found, and the merged layer product reports the number of cloud and aerosol layers found. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Interpretation of the number of layers found parameter is straightforward for the 1 km and 1/3 km layer products: individual layers are always separated by regions of "clear air", and layer boundaries never overlap in the vertical dimension. However, this simplicity of interpretation does not always carry over into the 5 km cloud and aerosol layer products. CALIPSO uses a nested multi-grid feature finding algorithm (see the layer detection ATBD), and thus the search for layer boundaries is conducted at multiple horizontal averaging resolutions. While the 1 km and 1/3 km layer products report only those features detected at, respectively, averaging resolutions of 1 km and 1/3 km, the 5 km products report layers detected at multiple averaging resolutions (5 km, 20 km, and 80 km in the version 3 products). Because the reporting resolution (5 km) is not always identical to the detection resolution, layers may appear to overlap in the vertical dimension.

Figure 2 shows a wholly fictitious but heuristically useful schematic of layer detection results for a data segment extending 80-km horizontally and 465-m vertically. Yellow/orange/brown colors indicate an aerosol layer detected at horizontal averaging resolutions of, respectively, 80, 20 or 5 km. Shades of blue likewise represent clouds detected at 80, 20, and 5 km resolutions. The white regions are (presumably) clear air, where no features were found. The labeled rows at the bottom indicate the 'number of layers found' that will be reported in the cloud and aerosol layer products for each 5 km column.

Figure 2: interpreting the number of layers parameters
Number Layers Found.

In column 16, the layer labeled F5 (top altitude = 0.285 km, base altitude = 0.165 km) appears to vertically overlap F6 (top altitude = 0.255 km, base altitude = 0.135 km), which in turn appears overlap F7 (top altitude = 0.225 km). However, F5 was detected at an averaging resolution of 5-km, and hence the backscatter data that comprises F5 is removed from consideration before construction the 20-km horizontally averaged profile in which F6 was detected. Similarly, the backscatter data from both F5 and F6 were removed from consideration before constructing the 80-km averaged profile in which F7 was detected. Layers detected at higher spatial resolutions are thus seen to overwrite, rather than overlap apparently collocated layers detected at coarser spatial resolutions. More details can be found in the Feature Detection and Layer Properties ATBD (PDF) and in Vaughan et al., 2009.


High_Resolution_Layers_Cleared (5 km products only)
Number of layers detected at single shot resolution which were cleared from the 5 km resolution column by the boundary layer cloud-clearing algorithm.

Single_Shot_Cloud_Cleared_Fraction (5 km products only)
Layers detected in the planetary boundary layer (PBL) are subjected to an additional cloud clearing procedure to separate small-scale boundary layer clouds from any surrounding PBL aerosols at the highest possible spatial resolution (i.e., single shot data). The single shot cloud cleared fraction reports the fraction of the nominal layer area (i.e., horizontal averaging distance times layer height) that was removed by the cloud clearing process. Details of the CALIPSO cloud clearing procedure can be found in the CALIPSO Feature Detection ATBD (PDF) and in Vaughan et al., 2009.

Was_Cleared (5 km and 1/3 products)
Single shot layers which were cleared by boundary layer cloud-clearing algorithm are flagged by the Was Cleared SDS. In the 5 km product, this flag is reported as ssWas_cleared in the Single Shot Detection Vgroup.

Layer Meteorological Properties


Layer_Top_Pressure
Pressure, in hPa, at the layer top altitude; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Midlayer_Pressure
Pressure, in hPa, at the geometric midpoint of the layer in the vertical dimension; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Layer_Base_Pressure (external)
Pressure, in hPa, at the layer top altitude; derived from the GEOS-5 data product provided to the CALIPSO project by the GMAO Data Assimilation System

Layer_Top_Temperature
Temperature, in degrees C, at the layer top altitude; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Layer_Centroid_Temperature (cloud and merged layer products only)
Temperature, in degrees C, at the layer attenuated backscatter centroid altitude; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Midlayer_Temperature
Temperature, in degrees C, at the geometric midpoint of the layer in the vertical dimension; derived from the MERRA-2 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Layer Base Temperature (external)
Temperature, in degrees C, at the layer base altitude; derived from the GEOS-5 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Relative_Humidity (5 km aerosol products only)
Relative humidity, in percent, at the geometric midpoint of the layer in the vertical dimension; derived from the GEOS-5 data product provided to the CALIPSO project by the GMAO Data Assimilation System. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Layer Measured Optical Properties


Integrated_Attenuated_Backscatter_532
The 532 nm integrated attenuated backscatter (hereafter, γ′532 or IAB) for any layer is computed according to equation 3.14 in section 3.2.9.1 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

For the uppermost layer in any column, the quality of the estimate for γ′532 is determined by the accuracy of the top and base identification, the reliability of the 532 nm channel calibrations, and by the signal-to-noise ratio (SNR) of the backscatter data within the layer. For layers beneath the uppermost, the quality of our estimate for γ′532 also depends on either obtaining an independent estimate of the two-way transmittance, T2, for all overlying layers, or by estimating this quantity directly from the lidar backscatter data. In those situations where an extended region of clear air exists between successive layers, and where the uppermost layer has no more than a moderate optical depth of -- say -- between 0.4 and 2.0, T2 can be estimated directly from the attenuated backscatter data (albeit with some uncertainty due to noise and the possibility of aerosol contamination of the clear air regions). Otherwise, the only way to estimate T2 is to compute a full extinction retrieval for the profile being examined. In this case, additional error can be introduced into the estimate of γ′532 by uncertainties in the approximation of the lidar ratio(s) for the overlying layer(s). Furthermore, the effects of errors caused by misestimating T2 can increase sharply as the optical thickness above a layer increases. For the 5 km layer products, the CALIOP processing scheme always attempts to correct estimates of γ′532 for the attenuation imparted by previously identified overlying features. As a consequence, we will occasionally report unrealistically large values for γ′532 in the 5 km layer products. However, because extinction solutions are only derived for data averaged to a 5-km (or greater) resolution, the γ′532 values reported in the 1 km and 1/3 km layer products are not corrected for the signal attenuation effects imparted by overlying layers.

The values reported for γ′532 should always be positive, and for the results derived directly from the layer detection algorithm (i.e., in the 1 km and 1/3 km layer products) this is indeed always true. However, in the 5 km products there are certain rare and pathological cases where a secondary layer could only be detected after averaging to 20 km or even 80 km horizontally, and where the overlying layers were detected at 5 km and have vastly different optical depths. In these cases, integrating the reaveraged data within the secondary layer will occasionally yield a negative γ′532. Such layers can be identified by a special CAD score of 105. All measured and derived optical properties for these layers are unreliable, and should be ignored. In evaluating the reliability of the spatial properties of these layers, users should carefully consider the layer IAB QA factor.


Integrated_Attenuated_Backscatter_Uncertainty_532
The uncertainties reported for the 532 nm integrated attenuated backscatters provide an estimate of the random error in the backscatter signal. The general procedure used for calculating uncertainties for integrated quantities is described by Liu et al., 2006 (PDF). The specific formula is given by equation 6.7 in the CALIPSO Feature Detection ATBD (PDF).

Attenuated_Scattering_Ratio_Statistics_532
This field reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the 532 nm attenuated scattering ratio coefficients for each layer, computed as the ratio of attenuated backscatter to molecular attenuated backscatter derived from MERRA-2 Molecular Number Density. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Attenuated_Backscatter_Statistics_532
This field reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the 532 nm attenuated backscatter coefficients for each layer. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Integrated_Attenuated_Backscatter_1064
The 1064 nm integrated attenuated backscatter (hereafter, γ′1064) for any layer is computed according to equation 6.6 in section 6.5 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

As is the case for γ′532, in the uppermost layer within any column, the quality of the estimate for γ′1064 is determined by the accuracy of the top and base identification, the reliability of the 1064 nm calibration constant, and by the signal-to-noise ratio (SNR) of the backscatter data within the layer. However, unlike the measurements at 532 nm, reliable estimates of T2 cannot be derived from an analysis of the 1064 nm backscatter signal in the (assumed to be) clear air regions, and thus in the 5 km products, the T2 corrections for the attenuation from overlying layers are always obtained from an extinction solution that uses prescribed values of the lidar ratios for all overlying layers. As is the case at 532 nm, no T2 corrections are applied to the γ′1064 values reported in the 1 km and 1/3 km layer products. Furthermore, because the CALIOP layer detection algorithm typically examines only the 532 nm backscatter signals, negative (i.e., non-physical) values may occasionally be reported for γ′1064 in all resolutions of the layer products. Unlike the layers for which γ′532 is negative, layers with negative γ′1064 are not indicated by a special CAD score. Negative values of γ′1064 occur most often for very weakly scattering layers (e.g., subvisible cirrus and faint aerosols) and in those layers for which the backscatter signal has been highly attenuated by other, overlying layers.


Integrated_Attenuated_Backscatter_Uncertainty_1064
The uncertainties reported for the 1064 nm integrated attenuated backscatter values provide an estimate of the random error in the backscatter signal. The general procedure used for calculating uncertainties for integrated quantities is described by Liu et al., 2006 (PDF). The specific formula is given by equation 6.7 in the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Attenuated_Backscatter_Statistics_1064
This field reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the 1064 nm attenuated backscatter coefficients for each layer. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF).

Integrated_Volume_Depolarization_Ratio
The layer integrated 532 nm volume depolarization ratio (hereafter, δv) is computed according to equation 6.10 in section 6.7 of the CALIPSO Feature Detection ATBD (PDF).

The quality of the estimate for δv is determined by the accuracy of the top and base identification, the reliability of the polarization gain ratio calibration, and by the signal-to-noise ratio (SNR) of the backscatter data within the layer. In general, the CALIOP δv estimates are highly reliable. Histograms of δv compiled for midlatitude cirrus in the northern hemisphere compare very well with previously reported distributions, e.g., Sassen & Benson, 2001 (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.


Integrated_Volume_Depolarization_Ratio_Uncertainty
The uncertainties reported for the 532 nm layer-integrated volume depolarization ratios provide an estimate of the total random error in the combined backscatter signals (i.e., the 532 nm parallel and perpendicular signals within the feature). The general procedure used for calculating uncertainties for integrated quantities is described by Liu et al., 2006 (PDF). The specific formula is given by equation 6.11 in the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Volume_Depolarization_Ratio_Statistics
This field reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the 532 nm volume depolarization ratios for each layer. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

In regions with acceptable SNR, the accuracy with which the range resolved depolarization ratios can be determined will depend almost entirely on the accuracy of the polarization gain ratio calibration.

Users can have high confidence in the calculation of all of the values in the depolarization ratio statistics fields. However, the meaning of these numbers can be somewhat obscure. This is because each of the range resolved depolarization ratios within any layer is the ratio of two noisy numbers. Especially where the feature is relatively faint, and in regions of low SNR, data values in both the numerator (the 532 nm perpendicular channel) and the denominator (the 532 nm parallel channel) can randomly and independently approach zero, which in turn can generate extremely large or extremely small (and even non-physical) depolarization ratios. When computing layer means, standard deviations, and centroids, these values can dominate the calculation, and thus return entirely unrealistic estimates. When assessing the depolarization ratio that characterizes a layer, δv and the layer median are both more reliable indicators than the mean.


Integrated_Attenuated_Total_Color_Ratio
The layer integrated attenuated total color ratio (hereafter, χ′layer) is computed according to equation 6.13 in section 6.7 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

The quality of the estimate for χ′layer is determined by the accuracy of the top and base identification, the reliability of the 532 nm calibration constant and the 1064 nm calibration constant, and by the signal-to-noise ratio (SNR) of the backscatter data within the layer. For the 5 km layer products, the attenuated backscatter coefficients used in the calculation of χ′layer are corrected for the estimated overlying two-way transmittance. No such correction is attempted for the 1 km and 1/3 km values, as no extinction solution is computed at these resolutions.


Integrated_Attenuated_Total_Color_Ratio_Uncertainty
The uncertainties reported for the layer-integrated attenuated total color ratios provide an estimate of the total random error in the combined backscatter signals (i.e., at 532 nm and 1064 nm). The general procedure used for calculating uncertainties for integrated quantities is described by Liu et al., 2006 (PDF). The specific formula is given by equation 6.14 in the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Attenuated_Total_Color_Ratio_Statistics
This field reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the attenuated total color ratios for each layer. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF). Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Users can have high confidence in the calculation of all of the values in the attenuated total color ratio statistics fields. However, as with the 532 nm depolarization ratio statistics, the meaning of the various numbers can be somewhat misleading. Like the depolarization ratios, the attenuated total color ratios are produced by dividing one noisy number (the 1064 nm attenuated backscatter coefficient) by a second noisy number (the 532 nm attenuated backscatter coefficient). Depending on the noise in any pair of samples, the resulting values can range from large negative values to extremely large positive values. When computing layer means, standard deviations, and centroids, these outliers can dominate the calculation, and thus return entirely unrealistic estimates.


Measured_Two_Way_Transmittance_532
Provides the measured value of the layer two-way transmittance (T2) for isolated transparent layers. In this context, an isolated layer is one that is not in contact with another layer or the surface at either its upper or lower boundaries. T2 is derived by computing the ratio of the mean attenuated scattering ratios in the "clear air" regions immediately below and above the layer. Details of the calculation are provided in the layer detection ATBD (PDF). This quantity is reported only for the 532 nm data, as the CALIOP 1064 nm channel is essentially insensitive to molecular backscatter. Physically meaningful measurements of two-way transmittance lie between 0 and 1; however, due to noise in the backscatter signal, and perhaps to undetected aerosol contamination of the "clear air" regions, the values reported in the CALIOP data products will sometimes exceed these bounds.

Measured_Two_Way_Transmittance_Uncertainty_532
The relative error in the two-way transmittance measurement, calculated using standard techniques for error propagation in ratioed quantities.


Two_Way Transmittance_Measurement_Region
Provides the base and top in km of the clear air region used to measure the two way transmittance below a transparent layer.

Opacity_Flag
In the context of the 5-km CALIOP layer products, a layer is considered opaque if (a) it is the lowest feature detected in a column, and (b) it is not subsequently classified as a surface return. An opacity flag value of 1 indicates an opaque layer; values of 0 indicate transparent layers. Users should be aware that the opacity flag does not indicate that an individual layer is actually opaque in the normal sense of the term. Instead, the opacity flag identifies that layer in which the backscatter signal becomes completely attenuated (i.e., indistinguishable from the background signal level). For those features having an opacity flag of 1, the reported base altitude must be considered as an apparent base, rather than a true base.

Because all features reported in 1/3-km and 1-km layer products are detected at a single horizontal averaging resolution (i.e., either at 1/3-km or 1-km), the opacity flag is not reported. When using these products, opacity, in the sense described above, can be assessed as follows. If the surface was detected (i.e., the lidar surface altitude field does not contain fill values) then there are no opaque layers in the column. If the surface was not detected, then the lowest layer in the column is considered to be opaque. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.


Layer Derived Optical Properties


Feature_Optical_Depth_532
Feature_Optical_Depth_1064
Reports estimates of layer optical depth computed according to the procedures outlined in the CALIOP extinction retrieval ATBD (PDF). Estimates for aerosol optical depths are provided at both wavelengths. Because the extinction coefficients for clouds are largely independent of wavelength in the spectral region sampled by CALIOP, cloud optical depth is reported only for the 532 nm measurements. When using any of these values in scientific studies, users are cautioned to take note of several important caveats:
  • For the vast majority of cases, CALIOP cannot provide a direct measurement of layer optical depth. In these cases, estimates of optical depth are derived using extinction-to-backscatter ratios (i.e., lidar ratios) that are specified based on an assessment of layer type and subtype. Uncertainties in the value of the lidar ratio, which can arise both from natural variability and from occasional misclassification of layer type, propagate non-linearly into subsequent estimates of layer optical depth.

  • Retrievals of optical depth from space-based lidar measurements must account for contributions from multiple scattering that are generally considered negligible in ground-based and aircraft based measurements. The theoretical basis for CALIPSO's treatment of multiple scattering is provided in the extinction retrieval ATBD (PDF) and in Winker, 2003 (PDF)

  • Similar to the layer detection problem, estimates of layer optical depth become increasingly fraught with error in multiple layer scenes, as errors incurred in overlying layers are propagated into the solutions derived for underlying features.

  • IMPORTANT NOTICE: before proceeding, all users of the CALIOP optical depth data should read and thoroughly understand the information provided in the Profile Products Data Quality Summary. This summary contains an expanded description of the extinction retrieval process from which the layer optical depths are derived, and provides essential guidance in the appropriate use of all CALIOP extinction-related data products.

Despite these caveats, users should not be unduly pessimistic about the quality and usability of the CALIPSO optical depth estimates. Figure 3 (below) shows a preliminary comparison of CALIPSO version 3 aerosol optical depths with the optical depths derived from MODIS for all daytime measurements acquired during January 2007. The comparison is generally good, with MODIS appearing to slightly over-estimate values at the lower end of the optical depth range.

Figure 3: Comparison of CALIPSO aerosol optical depths to those derived from MODIS
(Preliminary - January 2007, daytime data only) final lidar ratio = initial lidar ratio only)
A comparison plot of CALIPSO aerosol optical depths to those derived from MODIS.

Feature_Optical_Depth_Uncertainty_532
Feature_Optical_Depth_Uncertainty_1064
Estimated uncertainty in the layer optical depth at each wavelength, computed according to the formulas give in the CALIPSO Version 3 Extinction Uncertainty Document (PDF). Ignoring multiple scattering concerns for the moment, errors in layer optical depth calculations typically arise from three main sources: signal-to-noise ratio (SNR) within a layer, calibration accuracy, and the accuracy of the lidar ratio specified for use in the solution. Except for constrained solutions, where a lidar ratio estimate can be obtained directly from the attenuated backscatter data, lidar ratio uncertainties are almost always the dominant contributor to optical depth uncertainties, and the relative error in the layer optical depth will always be at least as large as the relative error in the layer lidar ratio, and will grow as the solution propagates through the layer and the layer two-way particulate transmittance decreases.

Calculation of the layer optical depth uncertainty is an iterative process. On some occasions when the SNR is poor, or an inappropriate lidar ratio is being used, the iteration will attempt to converge asymptotically to positive infinity. Whenever this situation is detected, the iteration is terminated, and the layer optical depth uncertainty is assigned a fixed value of 99.99. Any time an uncertainty of 99.99 is reported, the extinction calculation should be considered to have failed. The associated optical depths cannot be considered reliable, and should therefore be excluded from all science studies.

Note: optical depth uncertainties are reported as absolute errors, not relative errors.


Initial_532_Lidar_Ratio
Initial_1064_Lidar_Ratio
Retrieving optical depth and profiles of extinction and backscatter coefficients from the CALIOP measurements requires an estimate of the particulate extinction-to-backscatter ratio, which in the lidar community is commonly known as the "lidar ratio". These initial estimates are selected based on the type and subtype of the layer being analyzed. The values used in the current release are given below. Values highlighted in red have been changed since the version release.

Initial lidar ratios used in the version 4.10 extinction solver
Type Subtype Initial 532 nm lidar ratio Initial 1064 nm lidar ratio Reference
cloud water 19 ± 10 sr N/A  
cloud ice Sigmoid function of centroid temperature ± 10 sr N/A  
cloud unknown phase 22 ± 11 sr N/A  
tropospheric aerosol marine 23 ± 5 sr 23 ± 5 sr 2
tropospheric aerosol desert dust 44 ± 9 sr 44 ± 13 sr 3,4
tropospheric aerosol polluted continental/smoke 70 ± 25 sr 30 ± 14 sr 5
tropospheric aerosol clean continental 53 ± 24 sr 30 ± 17 sr 6
tropospheric aerosol polluted dust 55 ± 22 sr 48 ± 24 sr 7
tropospheric aerosol elevated smoke 70 ± 16 sr 30 ± 18 sr 3
tropospheric aerosol dusty marine 37 ± 15 sr 37 ± 15 sr 8
stratospheric aerosol PSC aerosol 50 ± 10 sr 50 ± 10 sr 9
stratospheric aerosol volcanic ash 44 ± 9 sr 44 ± 13 sr 10
stratospheric aerosol sulfate/other 50 ± 18 sr 30 ± 14 sr 11
stratospheric aerosol elevated smoke 70 ± 16 sr 30 ± 18 sr 3

(1) Constrained CALIPSO retrievals of high-confidence randomly oriented ice clouds (Garnier et al., 2016).
(2) HSRL measurements in multiple field campaigns, Müller et al. (2007). No wavelength dependence based on Sayer et al. (2012), Josset et al. (2012), Papagiannopoulos et al. (2016)
(3) CALIPSO constrained retrievals by Liu et al. (2014)
(4) HRSL measurements of transported Saharan dust. No wavelength dependence based on Tesche et al. (2009)
(5) Microphysical measurements made during NAMMA by Omar et al. 2010 and AERONET cluster analysis by Omar et al. 2005.
(6) HSRL measurements for layers classified as clean continental by CALIPSO (Rogers et al., 2014)
(7) Microphysical measurements made during NAMMA. Lidar ratio values in agreement with Papagiannopoulos et al. (2016) and Müller et al. (2007).
(8) Modeled mixture of dust and marine aerosol (65/35 by surface area). Uncertainty larger than dust or marine alone.
(9) Theoretical model of supercooled ternary solution at stratospheric pressures.
(10) CALIPSO dust lidar ratio used based on similarity with lidar ratios from Eyjafjallajokull volcano plume reported by Ansmann et al. (2012).
(11) Reference??

The initial lidar ratio for ice clouds has changed with version 4. It is now a sigmoid approximation function of the Layer_Centroid_Temperature which decreases from approximately 35 sr to 20 sr as cloud temperature decreases (https://doi.org/10.5194/amt-2018-182). Initial default version 4 lidar ratios are derived from the statistical analysis of several years of constrained retrievals, using only those clouds identified as high-confidence randomly oriented ice. The individual lidar ratios are retrieved from the layer apparent two-way transmittance, the layer-integrated attenuated backscatter, and the temperature-dependent multiple scattering factor. The resulting version 4 initial default 532 lidar ratio is a sigmoid approximation function of the Layer_Centroid_Temperature.

The initial lidar ratios and uncertainties for aerosols have also changed in version 4 for clean marine, dust, clean continental and elevated smoke subtypes to reflect the current state of knowledge based on observations by NASA Langley Airborne High Spectral Resolution Lidar, EARLINET, AERONET, CALIPSO and synergistic multi-sensor retrievals. Polluted dust lidar ratios remain the same as in version 3. The aerosol lidar ratios used for the CALIOP analyses represent well established mean values that are characteristic of the natural variability exhibited for each aerosol species (e.g., see Omar et al., 2005 (PDF); Cattrall et. al., 2005; and Figure 4 below). The clear implication of this natural variability is that even for those cases where the aerosol type is correctly identified, the initial lidar ratio represents an imperfect estimate of the layer-effective lidar ratio of any specific aerosol layer. These same caveats apply equally to the mean values used for the initial cloud lidar ratios. For all layer types, cloud-aerosol discrimination errors can exacerbate the error associated with the specification of the initial lidar ratio. Uncertainty can also be introduced by the cloud ice-water phase classification and the aerosol subtype identification procedures. However, the CALIOP extinction algorithm incorporates some error-correcting mechanisms that in many cases will adjust the initial estimate of lidar ratio so that a more suitable value is ultimately used in the retrieval. Details of the lidar ratio adjustment scheme are provided in the extinction retrieval ATBD (PDF). Algorithm architectural information and generalized error analyses for CALIPSO's cloud-aerosol discrimination algorithms, cloud ice-water phase algorithms, and aerosol subtyping algorithms can be found in the CALIPSO Scene Classification ATBD (PDF).


Final_532_Lidar_Ratio (5 km products only)
Final_1064_Lidar_Ratio 5 km aerosol products only)
This parameter reports the lidar ratio in use at the conclusion of the extinction processing for each layer. The final lidar ratio may be (1) the initial lidar ratio supplied by the Scene Classification Algorithms, (2) the result of modifications to this initial lidar ratio to avoid a non-physical solution, or (3) a lidar ratio determined from a measured layer transmittance. In cases where a suitable estimate of layer optical depth is available, the lidar ratio derived from that measurement will be used to generate the extinction solution. The extinction processing terminates when either a successful solution is obtained, or when the required adjustments to the lidar ratio exceed some predetermined bounds. Within those bounds, which range from 0 sr to 250 sr in the version 3.01 release, the extinction algorithm will, if necessary, adjust the initial lidar ratio as required to produce a physically plausible solution consistent with the measured data. Users can determine the status of the final lidar ratio by examining the extinction QC flags

For weakly scattering features, the lidar ratio is most often left unchanged by the extinction solver, as a physical solution is usually obtained on the first iteration. In these cases, the uncertainties in the final lidar ratio are the same as the uncertainties in the initial lidar ratio. The exception to this statement would be if either the cloud-aerosol discrimination or the layer sub-typing procedures have misclassified the layer. However, for weak layers, the relative error in the lidar ratio is (approximately) linearly related to the resulting error in the derived optical depth estimate.

Retrievals of opaque and strongly scattering layers are very sensitive to the initial lidar ratio selection. Too large a value will cause the retrieval algorithm to, in effect, extinguish all available signal before reaching the measured base of the feature. When that point is reached the retrieval becomes numerically unstable and the calculated extinction coefficients will asymptote toward positive infinity. In these cases, a successful solution can only be obtained by reducing the lidar ratio. The CALIOP extinction routine does this automatically, and will repeat the process until a stable solution is achieved. When this happens, the final lidar ratio reported in the data products is the first one for which a physically meaningful (albeit not necessarily correct) solution was obtained for the entire measured depth of the layer.

The optical depths and extinction profiles derived in those cases where the layer lidar ratio must be reduced are generally not accurate. The current lidar ratio reduction scheme terminates after identifying (a very close estimate of) the largest lidar ratio for which a physically meaningful solution can be generated for the backscatter measured in the layer. However, the optical depths and extinction profiles reported in these situations can only be considered as upper bounds; the true values are somewhat, or perhaps even significantly, lower. Because the associated optical depth uncertainties cannot be reasonably estimated, these data should be excluded from statistical analyses of layer optical properties, and even the most sophisticated users are advised to treat these cases with extreme caution.

When an independent estimate of layer optical depth is available from a measured layer two-way transmittance, the CALIOP extinction algorithm will retrieve the optimal estimate of the layer-effective lidar ratio, irrespective of layer type, and use this retrieved lidar ratio in the extinction retrieval. These so-called 'constrained' retrievals are more accurate than unconstrained retrievals. For constrained retrievals, the uncertainty in the final lidar ratio can be well estimated using equation 7.4 from the CALIPSO Scene Classification ATBD (PDF). An extinction QC value of 1 indicates a successful constrained retrieval.


Final_532_Lidar_Ratio_Uncertainty (5 km products only)
Final-1064_Lidar_Ratio_Uncertainty (5 km aerosol products only)
This parameter reports the lidar ratio uncertainty at the conclusion of the extinction processing for each layer.

Lidar_Ratio_532_Selection_Method (5 km products only)
Lidar_Ratio_1064_Selection_Method (5 km aerosol products only)
Specifies the internal procedure used to select the initial lidar ratio for each layer; valid values in this field are...

Value Method
0 not determined
1 constrained retrieval (using two-way transmittance)
2 based on cloud phase
3 based on aerosol species
99 fill value

Layer_Effective_532_Multiple_Scattering_Factor (5 km aerosol products only)
Layer_Effective_1064_Multiple_Scattering_Factor (5 km products only)
The layer effective multiple scattering factors, η532 and η1064, are specified at each wavelength according to layer type and subtype. Values range between 0 and 1; 1 corresponds to the limit of single scattering only, with smaller values indicating increasing contributions to the backscatter signal from multiple scattering. Multiple scattering effects are different in aerosols, ice clouds, and water clouds. A discussion of multiple scattering factors for ice clouds and several aerosol types can be found in Winker, 2003 (PDF). Multiple scattering in water clouds is discussed in Winker and Poole (1995).

Ice clouds: In Version 3 and earlier, ice clouds were assigned a range-independent multiple scattering factor of η532 = 0.6. Validation comparisons indicate this is an appropriate value and the same value is used in Version 3. In Version 4, the multiple scattering factor is instead implemented as a sigmoid approximation function of the layer attenuated backscatter centroid temperature, with η532 increasing from 0.46 at 270 K to 0.76 at 190 K. This approximation function was derived from extensive analysis of collocated measurements acquired by the CALIPSO lidar and the CALIPSO IIR, which reconciled observed and theoretical ratios (jason-please give link) of 532 nm optical depths derived from Version 3 CALIOP measured two-way transmittances to the absorption optical depth retrieved from IIR measurements at 12.05 μm. The theoretical ratios are computed assuming severely roughened aggregated columns (jason-please give link).

Water clouds: in Version 2 the multiple scattering factor for water clouds was set to unity, resulting in large errors in retrievals of extinction and optical depth. In Version 3, a value of η532 = 0.6 is used. Based on Monte Carlo simulations of multiple scattering, this value appears to be appropriate for semitransparent water clouds (τ < 1). (It is purely coincidental this is the same value used for ice clouds.) For denser water clouds (τ > 1) the multiply-scattered component of the signal becomes much larger than the single-scattered component, η532 becomes dependent on both cloud extinction and range into the cloud, and the retrieval becomes very sensitive to errors in the multiple scattering factor used. In these cases the multiple scattering cannot be properly accounted for in the current retrieval algorithm and retrieval results are unreliable.

Aerosols: simulations of multiple scattering effects on retrievals of aerosol layer optical depth indicate the effects are small in most cases. There is uncertainty in these estimates, however, due to poor knowledge of aerosol scattering phase functions. Validation comparisons conducted to date do not indicate significant multiple scattering effects on aerosol extinction profile retrievals. Multiple scattering effects may become significant in dense aerosol layers (σ > 1 /km), but in these cases retrieval errors are usually dominated by uncertainties in the lidar ratio or failure to fully penetrate the layer. In Version 3, as in Version 2, multiple scattering factors for both wavelengths are set to unity.


Integrated_Particulate_Depolarization_Ratio (5 km products only)
Similar to the layer-integrated volume depolarization ratio, except for particulates only. The particulate depolarization ratio represents the contribution to the volume depolarization ratio that is due only to the cloud and/or aerosol particles within the layer. For non-spherical particles (e.g., ice, dust) the particulate depolarization ratio will normally be higher than the volume depolarization ratio (how much higher depends on the particulate concentration within the volume). For layers consisting of spherical particles, the particulate depolarization ratio would normally be equal to or even slightly lower than the volume depolarization ratios. However, if the layer optical depth is high (e.g., water clouds), multiple scattering can cause the integrated particulate depolarization ratio to be substantially higher than otherwise expected.

While the volume depolarization ratio is a direct measurement, the layer integrated 532 nm particulate depolarization ratio, δp, is a post-extinction quantity, calculated from ratio of the layer integrated perpendicular and parallel polarization components of particulate backscatter coefficient within the layer, using

Particulate depolarization ratio equation.

Here β⊥,P and β||,P are the perpendicular and parallel components of particulate backscatter coefficient at 532 nm, respectively.

The quality of the estimate for δp is determined not only by the SNR of the backscatter measurements in parallel and perpendicular channels, but also the accuracy of the range-resolved two-way transmittance estimates within the layer. The two-way transmittances due to molecules and ozone can be well characterized via the model data obtained from the GMAO. The two-way transmittances due particulates, however, are only as accurate as the CALIOP extinction retrieval. Opaque cirrus cloud layers can be particularly prone to errors in the particulate depolarization ratio, as very large attenuation corrections are applied to the weak signals at the base of the layers, and on those occasions where one channel or the other becomes totally attenuated, this situation can generate very large, negative particulate depolarization ratio estimates. For layers that are not opaque, δp is generally reliable. However, in weakly scattering layers, the quality of the daytime estimate can be degraded by a factor of 2-4 due to the larger background noise compared with the nighttime estimate.


Integrated_Particulate_Depolarization_Ratio_Uncertainty (5 km products only)
Uncertainty associated with the estimate of the layer-integrated particulate depolarization ratio, calculated by integrating the uncertainties for the particulate backscatter coefficients measured in the 532 nm parallel and perpendicular channels, and then applying standard techniques for error propagation in ratioed quantities. The uncertainties for the parallel and perpendicular channel particulate backscatter coefficients are derived from previously computed estimates of the extinction uncertainty. There are occasions when the extinction uncertainty calculation can become unstable, and when this happens the calculated values begin to grow excessively large. Whenever this situation is detected, a default uncertainty of 99.99 is assigned to all remaining extinction and backscatter coefficients within a layer. If the extinction calculation anywhere within a layer found to be totally unreliable -- i.e., if the extinction uncertainty is 99.99 -- then the integrated particulate depolarization ratio must be considered equally unreliable. In these cases, the integrated particulate depolarization ratio uncertainty will also be set to 99.99.

Based on a one month test data set (January 2007), the median particulate depolarization ratio uncertainties in the aerosol layer products is typically ~0.04 and ~0.16 for nighttime and daytime measurements, respectively.

Note: both in the layer products and the profile products, particulate depolarization ratio uncertainties are reported as absolute errors, not relative errors.


Particulate_Depolarization_Ratio_Statistics (5 km products only)
Reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the array of particulate depolarization ratios computed for each layer. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF).

Integrated_Particulate_Color_Ratio (5 km aerosol products only)
The integrated particulate color ratio (hereafter, χp) is a post-extinction quantity, calculated from ratio of the particulate backscatter coefficients at wavelengths λ = 1064 nm and λ = 532 nm, each summed over the vertical extent of the layer; i.e.,

Particulate color ratio equation

Much like the integrated attenuated total color ratio, the quality of χp is governed by the accuracy to which layer top and base altitudes are determined and by the signal-to-noise ratios of the backscatter data within the layer. Additionally, since all of the βP,λ(z) values are derived by the Hybrid Extinction Retrieval Algorithm (HERA), the quality of χp also depends on the success of the HERA profile solver in deriving accurate solutions for βP,λ(z). As such, the quality of χp can be partially assessed via the extinction QC flags which report the final state of the HERA solution attempt. In general, solutions where the final lidar ratio is unchanged (extinction QC = 0) or the extinction solution is constrained (extinction QC = 1) yield physically plausible solutions more often. Conversely, solutions tend to be more uncertain in those cases where the lidar ratio for either wavelength must be reduced.


Integrated_Particulate_Color_Ratio_Uncertainty (5 km aerosol products only)
Uncertainty associated with the estimate of the layer-integrated particulate backscatter color ratio, calculated by first integrating the uncertainties for the particulate backscatter coefficients measured at each wavelength, and then applying standard techniques for error propagation in ratioed quantities. The error estimates in the particulate backscatter coefficients at both wavelengths are computed by the extinction retrieval algorithm. There are occasions when this calculation can become unstable, and the backscatter uncertainty calculation can grow excessively large. In these cases, a default uncertainty of 99.99 is assigned to all remaining backscatter coefficients (and extinction) coefficients within a layer. If the backscatter uncertainty calculation fails anywhere within a layer -- that is, if the uncertainty in any of the backscatter coefficients used to compute the particulate color ratio uncertainty is set to 99.99 -- then the particulate color ratio uncertainty for that layer will also be reported as 99.99.

Note: Uncertainties for layer-integrated particulate backscatter color ratios are reported as absolute errors, not relative errors.


Particulate_Color_Ratio_Statistics (5 km aerosol products only)
Reports the minimum, maximum, mean, standard deviation, centroid, and skewness coefficient of the array of particulate backscatter color ratios computed for each layer. Formulas used for each of the statistical calculations can be found in section 6 of the CALIPSO Feature Detection ATBD (PDF).

Users can have high confidence in the calculation of all the values in the attenuated particulate color ratio statistics fields. However, particulate color ratios are produced by dividing one noisy number (the 1064 nm mean particulate backscatter coefficient) by a second noisy number (the 532 nm mean particulate backscatter coefficient), resulting in values that can range from large negative values to extremely large positive values, depending on the noise in any pair of samples. When computing layer means, standard deviations, and centroids, these outliers can dominate the calculation, and thus return entirely unrealistic estimates. Therefore, the integrated particulate ratio characterizes the particulate color ratio of a layer more reliably than does the mean value of the individual particulate color ratios within a layer.


Ice_Water_Path (5 km cloud products only)
The integral, from layer top to layer base, of the ice-water content profile within any ice cloud layer. Ice water content is derived from the cloud particulate extinction coefficient using a temperature-dependent parameterization derived from in-situ measurements is discussed in Heymsfield et al. 2014.

Ice_Water_Path_Uncertainty (5 km cloud products only)
Uncertainty associated with the estimate of ice water path, computed by integrating the uncertainties computed for the ice water content within the layer. Because the ice water content is derived directly from the 532 nm extinction estimates, uncertainties in ice water path are directly related to uncertainties in layer optical depths. If the 532 nm optical depth for a layer is entirely uncertain (i.e., Δτ = 99.99), the ice water path uncertainty will also be entirely uncertain (i.e., ΔIWP = 99.99). The additional uncertainty in parameterizing IWC from extinction due to the aircraft in situ measurements is discussed in Heymsfield et al. 2014.

Cirrus_Shape_Parameter (5 km cloud products only)
Not calculated for the current release; data products contain fill values in this field.

Cirrus_Shape_Parameter_Invalid_Points (5 km cloud products only)
Not calculated for the current release; data products contain fill values in this field.

Cirrus_Shape_Parameter_Uncertainty (5 km cloud products only)
Not calculated for the current release; data products contain fill values in this field.

Layer QA Information

CAD_Score
The cloud-aerosol discrimination (CAD) score, which is reported in all layer products, provides a numerical confidence level for the classification of layers by the CALIOP cloud-aerosol discrimination algorithm. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution. The CAD algorithm separates clouds and aerosols based on multi-dimensional histograms of scattering properties (e.g., intensity and spectral dependence) as a function of geophysical location. In areas where there is no overlap or intersection between these histograms, features can be classified with complete confidence (i.e., |CAD score| = 100).

In the current release (version 4) the CAD algorithm uses five-dimensional (5D) probability density functions (PDFs),i.e. layer mean attenuated backscatter at 532 nm, layer-integrated attenuated backscatter color ratio, altitude, latitude and layer-integrated volume depolarization ratio. These PDFs were newly developed to take into account the significantly improved calibration of CALIOP version 4 level 1 data and using a latitude resolution of 5° (as opposed to 10° in earlier versions) leading to an overall improvement in CAD reliability. Detailed descriptions of the CAD algorithm can be found in Sections 4 and 5 of the CALIPSO Scene Classification ATBD (PDF). Further information on the CAD algorithm architecture may be found in Liu et al., 2010, 2009, 2004.

The CAD algorithm in version 4 is applied everywhere, including in the stratosphere and for the layers detected at single shot resolution (333m). The latter were classified as clouds by default in earlier versions and were removed before averaging over weaker signals at coarser resolution. However the users should note that the optical properties of these single shot layers were not used for building the CAD PDFs, which may affect the the overall CAD performance including the CAD scores for these single shot layers. Further, for scientific analysis using the Polar Stratospheric Clouds (PSCs), the users are strongly urged to use the dedicated PSC product from the CALIPSO data base.

The application of CAD everywhere led to two anomalous situations which needed special consideration. Firstly when dense smoke plumes occur over extended stratus and other water cloud layers, differential attenuation of the signals at 1064 nm and 532 nm can give very high color ratios resulting in very low CAD scores for the underlying clouds, even though they may be part of a larger cloud deck with high CAD score just outside the influence of the overhead smoke plume. In such cases, the color ratio is reset to an empirically derived climatological value and the CAD scores are recalculated. For such cases, the initial CAD score is also reported (in the cloud and merged layer products) along with the final CAD score. Secondly in a number of cases, isolated aerosol layers above 4 km appear adjacent to cirrus cloud layers either horizontally or vertically in locations where these aerosols are not expected. These are likely misclassified cirrus ("cirrus fringe") and were identified using a sequence of spatial proximity tests and were given a special CAD score of 106.

A more detailed description of the changes in the CAD scores from version 3 to version 4 is given in the version 4 data quality summary.

The standard CAD scores reported in the CALIPSO layer products range between -100 and 100. The sign of the CAD score indicates the feature type: positive values signify clouds, whereas negative values signify aerosols. The absolute value of the CAD score provides a confidence level for the classification. The larger the magnitude of the CAD score, the higher our confidence that the classification is correct. An absolute value of 100 therefore indicates complete confidence. Absolute values less that 100 indicate some ambiguity in the classification; that is, the scattering properties of the feature are represented to some degree in both the cloud PDF and in the aerosol PDF. In this case, a definitive classification cannot be made; that is, although we can provide a "best guess" classification, this guess could be wrong, with a probability of error related to the absolute value of the CAD score. A value of 0 indicates that a feature has an equal likelihood of being a cloud and an aerosol. Users are encouraged to refer to the CAD score when the cloud and aerosol classification results are used and interpreted.

Beginning with the version 2.01 release, several "special" CAD score values have been added. These are listed in the table below. Each of these new values represents a classification result that is based on additional information beyond that normally considered in the standard CAD algorithm.

CAD score Interpretation
-101 Negative mean attenuated backscatter encountered; layer is most likely an artifact, and its spatial and optical properties should be excluded from all science analyses.
103 Layer integrated attenuated backscatter at 532 nm is suspiciously high; feature authenticity and classification are both highly uncertain
104 Boundary layer clouds that were found to be opaque at the initial 5 km horizontal averaging resolution used by the layer detection algorithm; however, these layers are not uniformly filled with high-resolution clouds (i.e., layers detected at a 1/3-km horizontal resolution), and the 532 nm mean attenuated backscatter coefficient of the data that remains after cloud clearing is negative. Studies examining the spatial properties and distributions of clouds can safely include the spatial properties of these layers; however, the associated measured and derived optical properties should be excluded from all science studies.
105 Layer detected at one of the coarser averaging resolutions (20 km or 80 km) for which the initial estimates of measured properties have been negatively impacted by either (a) the attenuation corrections applied to account for the optical depths of overlying layers, or (b) the extension of the layer base altitude
106 Suspected fringe of cirrus initially classified as aerosol by the CAD algorithm and subsequently reclassified as no-confidence horizontally oriented ice cloud. These layers are in contact with cirrus (medium or high confidence, randomly or horizontally oriented ice clouds) and have optical properties which make it difficult to distinguish between cloud and aerosol. Due to their proximity to cirrus and low SNR, these layers are more often misclassified cirrus fringes and are thusly reclassified as cloud. Only aerosol layers detected at 20 km and 80 km resolution above 4 km in altitude and having layer centroid temperatures below 0°C are reclassified by the "cirrus fringe amelioration" algorithm.
Initial_CAD_Score
The cloud-aerosol discrimination (CAD) score, which is reported in the 1 km and 5 km layer products, provides a numerical confidence level for the classification of layers.

Extinction_QC_532 (5 km products only)
Extinction_QC_1064 (5 km aerosol products only)
The extinction QC flags are bit-mapped 16-bit integers, reported for each layer and for each wavelength for which an extinction retrieval was attempted. Aerosol extinction is computed for both wavelengths; cloud extinction is only reported at 532 nm. The information content of each bit is as follows

Bit Value Interpretation
1 0 unconstrained retrieval; initial lidar ratio unchanged during solution process
1 1 constrained retrieval
2 2 Initial lidar ratio reduced to prevent divergence of extinction solution
3 4 Initial lidar ratio increased to reduce the number of negative extinction coefficients in the derived solution
4 8 Calculated backscatter coefficient exceeds the maximum allowable value
5 16 Layer being analyzed has been identified by the feature finder as being totally attenuating (i.e., opaque)
6 32 Estimated optical depth error exceeds the maximum allowable value
7 64 Solution converges, but with an unacceptably large number of negative values
8 128 Retrieval terminated at maximum iterations
9 256 No solution possible within allowable lidar ratio bounds
16 32768 Fill value or no solution attempted

The bit assignments are additive, so that (for example) an extinction QC value of 18 represents an unconstrained retrieval (bit 1 is NOT set) for which the lidar ratio was reduced to prevent divergence (+2; bit 2 is set), and for which the feature finder has indicated that the layer is opaque (+16; bit 5 is set). For the version 2.01 release, bits 10-15 are not used. Complete information about the conditions under which each extinction QC bit is toggled can be found in the CALIPSO Extinction Retrieval ATBD (PDF).


Feature_Classification_Flags
For each layer, a set of feature classification flags are reported that provide assessments of (a) feature type (e.g., cloud vs. tropospheric aerosol vs. stratospheric aerosol); (b) feature subtype; (c) layer ice-water phase (clouds only); and (d) the amount of horizontal averaging required for layer detection. The complete set of flags is stored as a single 16-bit integer. A comprehensive description of the feature finder classification flags, including their derivation and physical significance, quality assessments, and guidelines for interpreting them in computer codes, can be found in the documentation for the vertical feature mask data product. Science data sets within the Single Shot Detection VGroup, also prefixed with "ss", report properties of features detected at single shot (1/3 km) resolution.

Correct interpretation of the feature subtype bits depends on the status of the feature type; e.g., the interpretation is different for clouds and aerosols. For tropospheric aerosols, the feature subtype is one of eight types: dust, elevated smoke, clean continental, polluted continental/smoke, clean marine, polluted dust, and dusty marine. Desert dust is mostly mineral soil. Elevated smoke is an aged smoke aerosol consisting primarily of soot and organic carbon (OC), clean continental (also referred to as background or rural aerosol) is a lightly loaded aerosol consisting of sulfates (SO42-), nitrates (NO3-), OC, and Ammonium (NH4+), polluted continental/smoke is background aerosol with a substantial fraction of urban pollution and/or smoke, marine is a hygroscopic aerosol that consists primarily of sea-salt (NaCl), and polluted dust is a mixture of desert dust and smoke or urban pollution and dusty marine is a mixture of dust and marine aerosol. While this set does not cover all possible aerosol mixing scenarios, it accounts for a majority of mesoscale aerosol layers. In essence the algorithm trades off complex transient multi-component mixtures for relatively stable layers with large horizontal extent (10-1000 km).


Layer_Type (5 km merged)
This SDS is the feature type from the feature classification flag, but only for 2-4.
  • 2 = cloud
  • 3 = aerosol
  • 4 = stratospheric aerosol

Layer_Base_Extended
A non-zero value indicates that the base of the layer has been extended from the initial altitude assigned by the layer detection algorithm to a new, lower altitude lying three range bins (90 m) above the Earth's surface. Non-zero values represent the layer's feature classification flags prior to the base being extended.

In Version 1 and 2 data, the base altitudes of optically thick aerosol layers were sometimes biased high due to lidar signal attenuation or signal perturbations, causing aerosol optical depth (AOD) underestimates. In Version 3, to compensate for this, layer base altitudes of aerosol layers meeting the following criteria (hereafter termed, 'extended layers') are lowered to three range bins (90 m) from the surface as reported by the lidar surface elevation. The criteria for aerosol layer base extension are:

  1. The layer must be the lowest layer in the 5 km resolution column
  2. The surface must be detected below the layer
  3. The difference between the original base altitude and Lidar Surface Elevation must be less than the science-tunable parameter, 'maximum gap distance', currently = 2.5 km
  4. The mean attenuated backscatter at 532 nm beneath the original base altitude must be positive

These criteria attempt to ensure that only boundary-layer aerosol layers with useable signals beneath their original bases are extended. The possibility of introducing surface contamination in layer optical properties is reduced by assigning the extended base to an altitude 90 m above the local surface height. Hence, surface contamination in extended layers is minimal and confined to regions with rugged terrain. However, this also means that profiles within layers with extended bases always stop 90 meters above the surface. In four months of global test data, the base altitudes of 8.6% of all layers originally classified as aerosol were extended, with average base altitudes lowered by 0.54 km.

Layer descriptors are re-computed after base extension and each extended layer is re-analyzed by the scene classification algorithms to assign feature type, subtype, and CAD Score. Consequently, the feature type or subtype of these layers may change since their optical properties have changed. Hence, layer base extended descriptors are populated with the feature classification flags of these layers prior to base extension so their previous type and subtype can be discerned. In four months of test data, 17% of extended aerosol layer subtypes changed due to base extension. Additionally, 12% of all extended aerosol layers were reclassified as cloud layers, accounting for 0.3% of all cloud layers. This typically occurs in scenes with low SNR, or when surface contamination is suspected. Extended aerosol layers which are reclassified as cloud layers tend to have very low CAD scores before and after base extension (65% have |CAD score| less than 10), so their type was never certain to begin with. These layers cannot be used with confidence. Conversely, 85% of extended layers have |CAD score| > 90 when the type does not change (extended aerosol layer remains an aerosol layer). Users are advised to consult CAD scores to assess confidence in all feature types.

Impact on Version 3 Aerosol Optical Depths

A focused study of two test days (2007-01-01 and 2007-08-27) found that the median optical depth of extended aerosol layers increased by 22%, resulting in a 1% AOD increase in all aerosol layers globally. The figure below shows the change in optical depth for extended aerosol layers (unconstrained retrievals) where the type or subtype did not change for the two test days. By design, optical depth values have increased due to the aerosol base extension algorithm.

Figure 6: Histogram of aerosol optical depth at 532 nm with and without
base extension for all extended aerosol layers in the two day test.
Aerosol optical depths with and without base extension.

Overlying_Integrated_Attenuated_Backscatter_(IAB)_532
Similar to the column integrated attenuated backscatter, the overlying integrated attenuated backscatter (hereafter, γ′above) is the integral with respect to altitude of the 532 nm total attenuated backscatter coefficients. The upper limit of integration is once again the first range bin in the measured signal profile, and the lower limit is now the range bin immediately above the layer top altitude.

γ′above provides a qualitative assessment of the confidence that users should assign to each layer reported. As noted earlier (see the discussion for layer base and top heights), layer detection, and the assessment of the associated layer descriptors, becomes increasingly uncertain as the overlying optical depth increases. This uncertainty cannot be easily quantified, because backscatter lidars such as CALIOP cannot measure optical depth directly, and must instead derive optical depth estimates in subsequent data processing. However, γ′above can easily be obtained directly from the calibrated backscatter signal, and hence can provide a qualitative proxy for the optical depth above each layer detected.


Layer_IAB_QA_Factor
The single layer analog of the column IAB cumulative probability; the layer IAB QA factor is defined as 1 - F(γ′above), where F(γ′above) is the cumulative probability of measuring a complete column integrated attenuated backscatter equal to γ′above.

File Metadata Parameters

Product_ID
an 80-byte (max) character string specifying the data product name. For all CALIPSO Level 2 lidar data products, the value of this string will be "L2_Lidar".

Date_Time_at_Granule_Start
a 27-byte character string that reports the date and time at the start of the file orbit segment (i.e., granule). The format is yyyy-mm-ddThh:mm:ss.ffffffZ.

Date_Time_at_Granule_End
a 27-byte character string that reports the date and time at the end of the file orbit segment (i.e., granule). The format is yyyy-mm-ddThh:mm:ss.ffffffZ.

Date_Time_at_Granule_Production
This is a 27-byte character string that defines the date at granule production. The format is yyyy-mm-ddThh:mm:ss.ffffffZ.

Number_of_Good_Profiles
This is a 32-bit integer specifying the number of good attenuated backscatter profiles contained in the granule.
NOTE: Currently not storing this value in this version of the data.

Number_of_Bad_Profiles
This is a 32-bit integer specifying the number of bad attenuated backscatter profiles contained in the granule.
NOTE: Currently not storing this value in this version of the data.

Initial_Subsatellite_Latitude
This field reports the first subsatellite latitude of the granule.

Initial_Subsatellite_Longitude
This field reports the first subsatellite longitude of the granule.

Final_Subsatellite_Latitude
This field reports the last subsatellite latitude of the granule.

Final_Subsatellite_Longitude
This field reports the last subsatellite longitude of the granule.

Orbit_Number_at_Granule_Start
This field reports the orbit number at the granule start time.

Orbit_Number_at_Granule_End
This field reports the orbit number at the granule stop time.

Orbit_Number_Change_Time
This field reports the time at which the orbit number changes in the granule.

Path_Number_at_Granule_Start
This field reports the path number at the granule start time.

Path_Number_at_Granule_End
This field reports the path number at the granule stop time.

Path_Number_Change_Time
This field reports the time at which the path number changes in the granule.

Lidar_Level_1_Production_Date_Time
For each CALIOP Lidar Level 2 data product, the Lidar Level 1 Production Date Time field reports the file creation time and date for the CALIOP Level 1 Lidar data file that provided the source data used in the Level 2 analyses.

Number_of_Single_Shot_Records_in_File
for internal use only

Number_of_Average_Records_in_File
for internal use only

Number_of_Features_Found
for internal use only

Number_of_Cloud_Features_Found
for internal use only

Number_of_Aerosol_Features_Found
for internal use only

Number_of_Indeterminate_Features_Found
for internal use only

Lidar_Data_Altitude
This field defines the lidar data altitudes (583 range bins) to which lidar Level 1 profile products are registered.

GEOS_Version
This is a 64-byte character that reports the version of the GEOS data product provided by the GMAO.

Classifier_Coefficients_Version_Number
Version number of the classifier coefficients file that stores the five-dimensional probability distribution functions used by the cloud-aerosol discrimination (CAD) algorithm

Classifier_Coefficients_Version_Date
Creation date of the classifier coefficients file that stores the five-dimensional probability distribution functions used by the cloud-aerosol discrimination (CAD) algorithm

Production_Script
Provides the configuration information and command sequences that were executed during the processing of the CALIOP Lidar Level 2 data products. Documentation for many of the control constants found within this field is contained in the CALIPSO Lidar Level 2 Algorithm Theoretical Basis Documents


Data Quality Statements

Lidar Level 2 Cloud and Aerosol Layer Information
Half orbit (Night and Day) lidar cloud and aerosol layer products describe both column and layer properties
Release Date Version Data Date Range Production Strategy
October 10, 2018
Standard Data
4.20 June 13, 2006 to present Standard
November 8, 2016
Standard Data
4.10 June 13, 2006 to May 31, 2018 Standard

Summary Statement for the release of the CALIPSO LIDAR Level 2 Products Version 4.20, October 10, 2018

View Detailed V4.20 Quality Statement.

Summary Statement for the release of the CALIPSO LIDAR Level 2 Products Version 4.10, November 08, 2016

View Detailed V4.10 Quality Statement.

NASA
Last Updated: October 01, 2021
Curator: Charles R. Trepte
NASA Official: Charles R. Trepte

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