We present the validation analysis of above-cloud aerosol optical depth
(ACAOD) retrieved from the “color ratio” method applied to MODIS cloudy-sky
reflectance measurements using the limited direct measurements made by NASA's
airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for
Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database
collection revealed a total of five significant events in which an airborne
sun photometer, coincident with the MODIS overpass, observed partially
absorbing aerosols emitted from agricultural biomass burning, dust, and
wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and
SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne
matchups revealed a good agreement (root-mean-square difference
Aerosol–cloud interaction continues to be one of the leading uncertain
components of climate models, primarily due to the lack of an adequate
knowledge of the complex microphysical and radiative processes associated
with the aerosol–cloud system
In the past few years, the development of several independent algorithms that
quantify aerosol loading above cloud from satellite-based active as well
passive measurements has been a major breakthrough in the fields of aerosol
and cloud remote sensing. These algorithms have shown the potential to
retrieve quantitative information on aerosol loading above cloud using
measurements from different A-train sensors including CALIOP/CALIPSO
Although the unprecedented quantitative information on aerosol loading above
cloud is now available from A-train sensors, an important question remains:
how do we validate the satellite retrievals of ACAOD? Unlike the validation
of cloud-free aerosol retrievals from satellites, for which ample
ground-based measurements are available, validation of ACAOD is a challenging
task primarily due to the lack of adequate direct measurements of aerosols in
cloudy skies, specifically of aerosols above cloud. The availability of
research-level retrievals of ACAOD from multiple sensors on the A-train
satellite constellation offers an opportunity to intercompare aerosol
loading derived using independent techniques applied to different sensors.
While ground-based measurements such as those from AERONET (Aerosol Robotic
Network) cannot be directly helpful in our situation, airborne measurements
taken when the aircraft is flying above cloud seem to be the only means to
validate the above-cloud aerosol retrievals. In pursuit of finding the right
dataset, we have looked at the data archive of past field campaigns with a
focus on aircraft-based direct measurements of AOD. We found that the
airborne measurements made by NASA's 6-14-channel Ames Airborne Tracking
Sunphotometer (AATS-6, -14) and their next generation sensor Spectrometer for
Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) provide a valuable
database for validating the satellite retrieval of ACAOD. The High Spectral
Resolution Lidar (HSRL) is another instrument which can measure the vertical
profile of particulate extinction without assuming a lidar ratio, and thus
can provide a direct measure of AOD above cloud provided that the HSRL flies
above the aerosol layer.
In this paper, we present the validation analysis of ACAOD retrieved from the MODIS sensor using cloudy-sky airborne measurements of AOD made by AATS and 4STAR. We mention here that we were unable to perform a validation analysis of OMI ACAOD retrieval due to two reasons: (1) four out of the five events of aerosols above clouds observed by AATS occurred prior to the launch of OMI in 2004, and (2) an event of wildfire smoke aerosols above clouds measured by 4STAR on 6 August 2013 was missed by OMI due to row anomaly contamination encountered during post-2008 operation. The rest of the paper is organized as follows: Sect. 2 introduces datasets and the co-location approach; results of satellite vs. airborne measurements are presented in Sect. 3; and a discussion of the uncertainties and future scope of validation study is presented in Sect. 4.
The 6- and 14-channel AATS developed by the NASA Ames research group
AATS has been
operated in several field campaigns, starting as early as July 1996 during
the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX),
and including the second Aerosol Characterization Experiment (ACE-2), South
African Regional Science Initiative (SAFARI) 2000
A thorough search of the AATS and 4STAR datasets
has revealed a total of five significant events of aerosols above cloud
observed during different field campaigns that are also co-located with the
MODIS overpasses. These include an event with carbonaceous aerosols
overlaying a marine boundary layer stratocumulus cloud deck over the
southeastern Atlantic Ocean on 13 September 2000 (AATS Flight no. 1837;
Aerosol properties assumed in the simulation of TOA reflectance lookup tables for different events of
aerosols above clouds discussed in the text. The assumed microphysical and optical properties were derived from
multi-year AERONET measurements at representative sites Mongu (15
The presence of an absorbing aerosol layer above cloud reduces the TOA
reflectance as well as color ratio between VIS and NIR wavelengths. The
general CR technique developed by
In contrast to the validation of cloud-free AOD retrieved from satellites, in
which columnar retrievals are compared against ground-based measurements
following a static spatiotemporal approach
Left: vertical profile of above-aircraft columnar AOD (500 nm) measured by AATS-14 during SAFARI-2000 flight UW1837, which flew on 13 September 2000 over Walvis Bay. Right: altitude dependence of ratio of AOD at 900 hPa to AOD at different pressure levels measured during the same flight.
Figure
Statistical summary of the MODIS vs. airborne above-cloud AOD comparison.
Top: true-color RGB images captured by MODIS superimposed with AOD (500 nm) measured by AATS-6,-14/4STAR on 13 September 2000, 20, 30 April 2001, and 6 August 2013 during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013, respectively. Bottom: spatial distribution of above-cloud AOD (500 nm) retrieved from MODIS for the respective dates.
Figure
The presence of absorbing aerosols above
cloud obstructs the light reflected by the cloud top, and thus reduces
upwelling UV, VIS, and NIR radiation reaching the TOA. Therefore, cloud
retrievals of COD derived from passive sensors such as MODIS are expected to
be biased low if absorbing aerosols are not accounted for in the inversion
Left: scatter plot of above-cloud AOD retrieved from MODIS (
Although the satellite retrieval of ACAOD is found to be in good agreement
with airborne measurements, some discrepancies remain. The CR algorithm makes
assumptions about properties of aerosol and cloud in order to perform
inversion from satellite observations. Two most important assumptions made in
the algorithm are the value of the imaginary part of refractive index, which
for a given particle size distribution can be expressed as SSA, and vertical
profiles of clouds and aerosols. The theoretical uncertainty analysis adopted
for the MODIS wavelengths suggests that, while an uncertainty of
The absorption properties assumed in the aerosol models (Table
Besides algorithmic assumptions, the comparison of airborne measurements
vs. satellite retrievals can also be affected by the effectiveness of
co-location methodology. First, the time difference between the satellite
overpass time and AATS/4STAR measurements ranges from 30 min to 4 h (Table 2), which is larger than the typical time window of 30 min
adopted in the validation exercise of the clear-sky satellite
products. Any changes in the aerosol and cloud fields between the time domain
of airborne measurements and satellite retrievals will inevitably introduce
a mismatch in the comparison. Second, the scaling procedure described in
Sect. 2.3 relies on a single profile of AOD measured during respective
fights and assumes its validity along the entire path of aircraft sortie.
While the information on vertical structure of aerosols outside the region of
profile measurements is not known, deviation from the assumed profile of AOD
can also add uncertainty in the AOD scaled to the cloud top pressure. Third,
the scaling of AOD involves the use of MODIS-retrieved cloud top pressure, which is uncertain to within
The main purpose of the validation exercise, such as presented in this paper, is to assess the accuracy of the satellite-based retrievals given the algorithmic assumptions about aerosol and cloud models. It is expected that using the “true” values of aerosol microphysical and optical properties for the present case studies will provide more accurate retrievals. However, we emphasize that despite the multi-year approach adopted here for developing aerosol models and inherent uncertainty in the co-location procedure, MODIS retrievals of ACAOD are in overall good agreement with the airborne direct measurements within the expected uncertainty limits. This by itself provides an indirect assessment of the assumptions made in the inversion process, which seem to be working reasonably well for the present case studies.
The present paper has attempted to validate the satellite retrieval of ACAOD using a limited set of airborne sun photometer measurements. We emphasize here that this work is just the beginning of a continuing exercise of evaluating space-based characterization of aerosols above cloud. Past field campaigns focused on characterizing aerosol properties in cloud-free regions in order to evaluate and improve satellite-based retrievals, but this left vast cloudy areas unmonitored in terms of aerosol measurements. Now satellite-based remote sensing techniques using passive sensors are beginning to quantitatively retrieve aerosol loading above cloud over a large spatial domain; however validation of these retrievals will remain incomplete without the availability of adequate and accurate airborne measurements.
NASA's ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS;
In parallel with ORACLES, the Cloud Aerosol Radiation Interactions and Forcing: Year 2016 (CLARIFY-2016) campaign with project partners from the UK Met Office and universities will also take place over the same region with deployment of airborne and surface-based instruments in conjunction with satellite observations of aerosols and clouds. Both of these planned high-profile experiments will deliver a wide range of direct and in situ observations of aerosol above clouds to provide a better process-level understanding of aerosol–cloud–radiation interactions over the SE Atlantic. Among the planned measurements, direct AOD and detailed optical and microphysical measurements of aerosols above cloud will be germane for validating and improving satellite-based retrievals. For instance, the microphysical models, in particular the imaginary part of refractive index and SSA assumed in the satellite-based inversion, pose the largest source of uncertainty in the retrieval. Observations from ORACLES and CLARIFY-2016 will challenge and improve these models for achieving better accuracy in the satellite retrieval.
In addition to the validation activities, intercomparison of retrievals from A-train sensors should be carried out on various spatial and temporal scales and over distinct hot spot regions of the world, where the overlap of absorbing aerosols and cloud is observed frequently. This is needed to better understand the relative strengths and weaknesses of each sensor and to check the inter-consistency between them. Currently, all ACAOD retrievals are research-only algorithms, but we expect as these algorithms are better understood they could evolve into deliverable operational or semi-operational products on a global scale in the coming years. True validation exercises, such as the opportunities to compare retrievals with a high-quality airborne instrument as presented here, are essential components in providing the confidence needed towards moving algorithms into operations. A global above-cloud aerosol product, in conjunction with standard cloud-free aerosol products derived from satellites, will provide us an unprecedented all-sky aerosol distribution from space. This can substantially enhance our knowledge on how aerosols affect cloud radiative forcing and microphysical properties, and aerosol transport.
The direct measurements of aerosol optical depth made by airborne AATS and 4STAR sunphotometers were accessed from
MODIS Level 1 data were obtained from
MODIS above-cloud aerosol optical depth data were retrieved using a research-level stand-alone algorithm described in Jethva et al. (2013).
We acknowledge the support of the LAADS team for online availability of the MODIS dataset. We also extend our thanks to the principal investigators of AERONET sites for providing the data that were used to build the aerosol models required for this analysis. The leading author thanks members of the NASA AATS and 4STAR teams for making valuable airborne measurements during different field campaigns, which served as a validation database for accessing the satellite-retrieved above-cloud AOD. Edited by: A. Kokhanovsky Reviewed by: A. M. Sayer and three anonymous referees