Detailed Quality Document for the CALIPSO Version 4.20 IIR Level 2 Track and Swath Data Products
Last Updated: April 28, 2020
Last Updated: October 11, 2020
Data Release Date:
April 27, 2020
Data Release Date:
October 12, 2020
Data Date Range:
June 13, 2006 to June 30, 2020
Data Date Range:
July 01, 2020 to present
10-01-2020: Version 4.21
A minor version bump (+0.01) has been applied to all CALIPSO data products due to
a required upgrade to the operating system on the CALIPSO production cluster. All
algorithms were re-compiled to process in this new environment with no change to
the underlying science algorithms or inputs.
The IIR Level 2 algorithm, described in details in Garnier et al.
takes full advantage of the co-located characterization of the atmosphere provided
by CALIOP. It is applied to suitable types of scenes classified using the V4.20 CALIOP
5-km Cloud and Aerosol layer products. The retrievals are applied to the so-called upper
level cloud which includes either one single semi-transparent or opaque layer, or
several semi-transparent layers.
Effective emissivity retrievals require i) a correction for the contribution
from the “background” and ii) the determination of the radiative temperature of
the upper level cloud. When the lowermost of at least two individual cloud layers
in the column is opaque to CALIOP, the background reference is from this opaque
layer, which is called lower level. Otherwise, the background reference is from
the Earth surface in clear air conditions. Both in V3 and in V4, the first step
into the computation of the radiative temperature is to determine the centroid
altitude of the upper level cloud.
As in V3, ice cloud effective diameter (De) retrievals use the concept
of microphysical index (ßeff) applied to the IIR pairs of channels
(12.05, 10.6) and (12.05, 8.65), with ßeff12/10 and ßeff12/08
defined as the 12.05-to-10.6 and 12.05-to-08.65 ratios of the effective absorption
optical depths, respectively. The microphysical indices are interpreted in terms of
De by using Look-Up Tables (LUTs) built for several models. The ice water
path is then determined from calculated effective emissivities and De.
The most significant changes in the V4 algorithm include:
A refined scene classification
An updated radiative transfer model analysis for clear air reference with new surface emissivity values and corrected land surface temperature
A revised centroid altitude in multi-layer cases
Refined radiative temperature estimates in ice clouds
Updated and extended microphysical retrievals in ice clouds
Addition of microphysical retrievals in liquid water clouds
Revised uncertainty estimates
Refined Scene Classification
In V4, a new “Was_Cleared_Flag_1km” parameter reports the number
of clouds seen by the 1-km IIR pixel that were detected by CALIOP at single shot
resolution and that were
cleared from the CALIOP 5-km layer products.
These clouds have a top altitude < 4 km. In V3, these single-shot cleared clouds
were not reported in the CALIOP 5-km layer products and they were ignored by the
In V4, the cloud-free (clear sky or aerosol only) scenes must have Was_Cleared_Flag_1km = 0.
When Was_Cleared_Flag_1km ≠ 0, these scenes, which were thought to be cloud-free
in V3, are assigned new types of scenes in V4.
For effective emissivity retrievals, the background radiance is computed regardless
of Was_Cleared_Flag_1km. Unless the bias in the background radiance due to the cleared
clouds can be estimated a posteriori and can be deemed acceptable, it is recommended
to ensure that Was_Cleared_Flag_1km = 0 for detailed analyses of retrievals in
optically thin clouds.
For the scenes that fall into the “clouds” category, the semi-transparent
aerosol layers, if any, are ignored when computing the cloud effective emissivity.
In V4, we require that the “clouds” scenes that contain only one or two semi-transparent
cloud layers do not contain high (typically stratospheric) aerosol layers, because
these high aerosol layers could absorb in the IIR channels.
In addition, the presence of potentially absorbing aerosol layers
(i.e. tropospheric dust or stratospheric aerosols) is now reported in a new
Dust_Stratospheric_Aerosol_Flag and a new Dust_Stratospheric_Aerosol_Flag_QA so
that the retrievals can be filtered using these flags.
Updated Radiative Transfer Model Analysis for Clear Air Reference
When no relevant neighboring observations can be found, the background reference
is computed using a radiative transfer model, meteorological profiles and surface
temperature from MERRA-2 re-analyses, and surface emissivity values.
The radiative transfer model has been updated in V4 to better simulate absorption by water vapor.
Surface Category, Surface Emissivity, and Surface Temperature
In V3, the surface emissivity values in each IIR channel were theoretical static
values assigned to each IGBP Surface Type. When the daily Snow_Ice_Surface_type
indicated the presence of snow or sea ice, IGBP Surface Type was changed to
IGBP = 15 (snow/ice).
In V4, the characterization of the surface has been refined, and is reported in
a new “TGeotype” parameter. TGeotype is assigned using IGBP Surface
Type and the co-located Surface_532_Integrated_Depolarization_Ratio, now reported
in the V4 CALIOP products, and Snow_Ice_Surface_type if Surface_532_Integrated_Depolarization_Ratio
is not available. Surface_532_Integrated_Depolarization_Ratio is also used to refine the
land/water classification around coastlines. The TGeotype values fall into five main
categories: water, water/sea ice transition, sea ice, snow, and snow-free land.
Surface emissivity values used in V4 have been determined empirically from the
analysis of two years of IIR data in clear sky conditions. The V4 algorithm continues
to use static values for the water, water/sea ice transition, sea ice, and snow
categories. For the snow-free land category, the V3 static values per IGBP type at
08.65 μm and 10.6 μm are replaced with monthly daytime and nighttime maps
(resolution: latitude x longitude = 1° x 2°), while a constant value (0.975)
is taken at 12.05 μm. In case of snow-free land, the surface temperature is the
initial MERRA 2 surface temperature further corrected using monthly daytime and
nighttime correction maps that were derived using the 12.05 μm reference channel
by reconciling calculations and IIR observations.
Summary of Clear Air Reference Changes from V3 to V4
The changes described above improve the accuracy of effective emissivity and
microphysical retrievals in optically thin layers when the clear air background
radiance is derived from the model. Subsequently, retrievals derived from observed
and computed background radiances are more consistent in V4 than in V3.
Over oceans, the change from V3 to V4 is for the most part the reduction of
systematic effective emissivity biases at 08.65 μm, which improves the reliability
of effective diameter retrievals. Even though less accurate than over oceans,
retrievals over land are improved in V4, in particular in desertic areas and in
Revised Centroid Altitude in Multi-layer Cases
Because of an error in the V3 algorithm, the centroid altitude of multi-layer
systems could be too low by up to 3 km in V3. This has been fixed in V4.
Refined Radiative Temperature Estimates in Ice Clouds
In V3, the radiative temperature was set to the temperature at the lidar centroid
altitude for any cloud or aerosol system. The approach is the same in V4, except
when all the layers are classified as ice by the V4 CALIOP ice/water phase algorithm.
In the latter case, the initial centroid temperature estimate (which was used in V3)
has been shown to be cold
(Garnier et al., 2015).
It is now refined in V4 using parameterized correction functions. Blackbody brightness
temperatures derived from both the centroid temperature and the V4 radiative
temperature are reported in the V4 product.
The correction applied in V4 has a negligible impact on effective emissivity
values smaller than about 0.3. The largest impact is for opaque clouds, the correction
being more efficient for nighttime than for daytime data. For instance, for oceanic
opaque ice clouds in January 2008, nighttime and daytime distributions of effective
emissivity at 12.05 μm peak respectively at 0.99 and 0.97 in V4, compared to 0.94 in V3.
Updated Microphysical Retrievals in Ice Clouds
The three ice crystal models used in V3 have been replaced with two ice crystal
models in V4, namely severely rough “single hexagonal column” and
“8-element column aggregate” elaborated from new ice properties
(Yang et al., 2013;
Bi and Yang, 2017).
In addition, a gamma particle size distribution with effective variance equal to
0.1 is taken in V4, whereas there was no size distribution in V3. As a result of
these changes, De is increased from V3 to V4.
Four independent sets of De derived from a second approach are also reported in V4.
This approach uses analytical functions relating ßeff12/10 and
De as derived from in situ measurements at tropical and mid-latitudes
performed during the TC4 and SPARTICUS field experiments
(Mitchell et al., 2018).
Ice Water Path
For ice clouds, Ice Water Path is estimated from De and visible extinction optical depth
(τvis) derived from calculated effective emissivities. In V3,
τvis was approximated to 2τa,12, where τa,12
is the IIR affective absorption optical depth at 12.05 μm. In V4, τvis is approximated to
τa,12 + τa,10, where τa,10 is the IIR
affective absorption optical depth at 10.6 μm. The V4 approximate reduces the
dependence on De and improves the τvis estimate by up 10 % for De > 20 μm.
Addition of Microphysical Retrievals In Liquid Water Clouds
Unlike in V3, microphysical retrievals in liquid water clouds are provided in V4.
For De retrievals, the LUTs are computed using the Mie theory
with refractive indices from
Hale and Querry (1973)
and again using a gamma particle size distribution (PSD) with effective variance
equal to 0.1. No temperature dependence of infrared absorption is included.
Liquid Water Path is estimated from De, τa,12, and
Qa,12(De), where the latter is the effective absorption efficiency
at 12.05 μm, whose variation with De ≤ 20 μm is represented
using a fourth-degree polynomial. In agreement with
Pinnick et al. (1979),
Qa,12 increases quasi-linearly with De < 10 μm up to
about 1, and then increases slowly up to 1.15 as De increases from 10 to 20 μm.
Revised Uncertainty Estimates
Effective Emissivity Uncertainty
For each IIR channel, the estimated uncertainty in the effective emissivity is composed of three terms associated to
an error dTm in the measured brightness temperature,
an error dTBG in the background reference brightness temperature,
an error dTBB in the blackbody temperature.
In V3, the reported uncertainties were computed using
dTm = dTBG = dTBB = 1 K.
The following temperature errors are used in V4:
In V4, the three terms used to compute the estimated uncertainty in the effective emissivity are reported.
Effective Diameter Uncertainty
The approach chosen to report the estimated uncertainty in De has
been changed in V4. In V4, it is simply inferred from the estimated uncertainty
in the microphysical indices and from the LUT used for the retrievals.
Ice or Liquid Water Path Uncertainty
Unlike in V3, an estimated uncertainty in the ice or liquid water path is reported
in V4. It is computed from the estimated uncertainty in De and in the
effective absorption optical depth(s).
Last Updated: March 23, 2021
Curator: Charles R. Trepte
NASA Official: Charles R. Trepte