scholarly journals Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

2020 ◽  
Vol 12 (23) ◽  
pp. 3987
Author(s):  
Sujung Go ◽  
Jhoon Kim ◽  
Sang Seo Park ◽  
Mijin Kim ◽  
Hyunkwang Lim ◽  
...  
Keyword(s):  
Spatial Data ◽  
Estimation Method ◽  
Weighting Factor ◽  
Data Availability ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Uv Visible ◽  
Type Classification ◽  
Aerosol Type

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet (UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of >~0.4 and GEMS SSA values of <~0.95. Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

scholarly journals Improvements to the OMI near UV aerosol algorithm using A-train CALIOP and AIRS observations

2013 ◽  
Vol 6 (3) ◽  
pp. 5621-5652 ◽  
Author(s):  
O. Torres ◽  
C. Ahn ◽  
Z. Chen
Keyword(s):  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Carbonaceous Aerosols ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Layer Height ◽  
Aerosol Retrieval ◽  
Polarization Sensor ◽  
Aerosol Properties

Abstract. The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in determining the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the use of this information as input to the OMI (Ozone Monitoring Instrument) near UV aerosol retrieval algorithm (OMAERUV). A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) CO observations are used in an upgraded version of the OMAERUV algorithm. AIRS CO measurements are used as a reliable tracer of carbonaceous aerosols, which allows the identification of smoke layers in regions and seasons when the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of elevated levels of boundary layer pollution undetectable by near UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show an improvement in OMI aerosol retrieval capabilities.

scholarly journals Improvements to the OMI near-UV aerosol algorithm using A-train CALIOP and AIRS observations

2013 ◽  
Vol 6 (11) ◽  
pp. 3257-3270 ◽  
Author(s):  
O. Torres ◽  
C. Ahn ◽  
Z. Chen
Keyword(s):  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Carbonaceous Aerosols ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Layer Height ◽  
Aerosol Retrieval ◽  
Polarization Sensor ◽  
Aerosol Properties

Abstract. The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in determining the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near-UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the use of this information as input to the OMI (ozone monitoring instrument) near-UV aerosol retrieval algorithm (OMAERUV). A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) observations are used in an upgraded version of the OMAERUV algorithm. AIRS CO measurements are used as an adequate tracer of carbonaceous aerosols, which allows the identification of smoke layers in regions and seasons when the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of high levels of boundary layer pollution undetectable by near-UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show an improvement in OMI aerosol retrieval capabilities.

scholarly journals CALIOP near-real-time backscatter products compared to EARLINET data

2015 ◽  
Vol 15 (5) ◽  
pp. 6041-6075
Author(s):  
T. Grigas ◽  
M. Hervo ◽  
G. Gimmestad ◽  
H. Forrister ◽  
P. Schneider ◽  
...  
Keyword(s):  
Real Time ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Orthogonal Polarization ◽  
Lidar Data ◽  
Aerosol Layer ◽  
Complete Dataset ◽  
Aerosol Classification ◽  
Ground Based Lidar ◽  
Aerosol Type

Abstract. The expedited near-real-time Level 1.5 Cloud–Aerosol Lidar (Light Detection and Ranging) with Orthogonal Polarization (CALIOP) products were evaluated against data from the ground-based European Aerosol Research Lidar Network (EARLINET). Over a period of three years, lidar data from 48 CALIOP overpasses with ground tracks within a 100 km distance from an operating EARLINET station were deemed suitable for analysis and they included a valid aerosol classification type (e.g. dust, polluted dust, clean marine, clean continental, polluted continental, mixed and/or smoke/biomass burning). For the complete dataset comprising both PBL and FT data, the correlation coefficient was 0.86, and when separated into separate layers, the PBL and FT correlation coefficients were 0.6 and 0.85 respectively. The presence of FT layers with high attenuated backscatter led to poor agreement in PBL backscatter profiles between the CALIOP and EARLINET measurements and prompted a further analysis filtering out such cases. However, the correlation coefficient value for the complete dataset decreased marginally from 0.86 to 0.84 while the PBL coefficient increased from 0.6 up to 0.65 and the FT coefficient also decreased from 0.85 to 0.79. For specific aerosol types, the correlation coefficient between CALIOP backscatter profiles and ground-based lidar data ranged from 0.37 for polluted continental aerosol in the planetary boundary layer (PBL) to 0.57 for dust in the free troposphere (FT). The results suggest different levels of agreement based on the location of the dominant aerosol layer and the aerosol type.

scholarly journals The role of cloud contamination, aerosol layer height and aerosol model in the assessment of the OMI near-UV retrievals over the ocean

2016 ◽  
Vol 9 (7) ◽  
pp. 3031-3052 ◽  
Author(s):  
Santiago Gassó ◽  
Omar Torres
Keyword(s):  
Particle Shape ◽  
Spherical Shape ◽  
Detailed Examination ◽  
Index Of Refraction ◽  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Aerosol Model ◽  
Modis Aod

Abstract. Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD < 0.3, 30 % for AOD > 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm  ∼  < 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

scholarly journals The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and evaluation

2019 ◽  
Vol 12 (7) ◽  
pp. 3673-3698 ◽  
Author(s):  
Sieglinde Callewaert ◽  
Sophie Vandenbussche ◽  
Nicolas Kumps ◽  
Arve Kylling ◽  
Xiaoxia Shang ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Estimation Method ◽  
Dust Aerosol ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Concentration Profiles ◽  
Qualitative Comparison ◽  
Data Set ◽  
The Mean ◽  
Infrared Radiances

Abstract. The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm retrieves vertical dust concentration profiles from cloud-free Infrared Atmospheric Sounding Interferometer (IASI) thermal infrared (TIR) radiances using Rodgers' optimal estimation method (OEM). We describe the new version 4.1 and evaluation results. Main differences with respect to previous versions are the Levenberg–Marquardt modification of the OEM, the use of the logarithm of the concentration in the retrieval and the use of Radiative Transfer for TOVS (RTTOV) for in-line radiative transfer calculations. The dust aerosol concentrations are retrieved in seven 1 km thick layers centered at 0.5 to 6.5 km. A global data set of the daily dust distribution was generated with MAPIR v4.1 covering September 2007 to June 2018, with further extensions planned every 6 months. The post-retrieval quality filters reject about 16 % of the retrievals, a huge improvement with respect to the previous versions in which up to 40 % of the retrievals were of bad quality. The median difference between the observed and fitted spectra of the good-quality retrievals is 0.32 K, with lower values over oceans. The information content of the retrieved profiles shows a dependence on the total aerosol load due to the assumption of a lognormal state vector. The median degrees of freedom in dusty scenes (min 10 µm AOD of 0.5) is 1.4. An evaluation of the aerosol optical depth (AOD) obtained from the integrated MAPIR v4.1 profiles was performed against 72 AErosol RObotic NETwork (AERONET) stations. The MAPIR AOD correlates well with the ground-based data, with a mean correlation coefficient of 0.66 and values as high as 0.88. Overall, there is a mean AOD (550 nm) positive bias of only 0.04 with respect to AERONET, which is an extremely good result. The previous versions of MAPIR were known to largely overestimate AOD (about 0.28 for v3). A second evaluation exercise was performed comparing the mean aerosol layer altitude from MAPIR with the mean dust altitude from Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP). A small underestimation was found, with a mean difference of about 350 m (standard deviation of about 1 km) with respect to the CALIOP cumulative extinction altitude, which is again considered very good as the vertical resolution of MAPIR is 1 km. In the comparisons against AERONET and CALIOP, a dependence of MAPIR on the quality of the temperature profiles used in the retrieval is observed. Finally, a qualitative comparison of dust aerosol concentration profiles was done against lidar measurements from two ground-based stations (M'Bour and Al Dhaid) and from the Cloud–Aerosol Transport System (CATS) instrument on board the International Space Station (ISS). MAPIR v4.1 showed the ability to detect dust plumes at the same time and with a similar extent as the lidar instruments. This new MAPIR version shows a great improvement of the accuracy of the aerosol profile retrievals with respect to previous versions, especially so for the integrated AOD. It now offers a unique 3-D dust data set, which can be used to gain more insight into the transport and emission processes of mineral dust aerosols.

scholarly journals Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI

2016 ◽  
Vol 16 (1) ◽  
pp. 47-69 ◽  
Author(s):  
R. Alfaro-Contreras ◽  
J. Zhang ◽  
J. R. Campbell ◽  
J. S. Reid
Keyword(s):  
Interannual Variability ◽  
Orthogonal Polarization ◽  
Cloud Detection ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
First Time ◽  
Aerosol Index

Abstract. Seven and a half years (June 2006 to November 2013) of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol and cloud layer products are compared with collocated Ozone Monitoring Instrument (OMI) aerosol index (AI) data and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products in order to investigate variability in estimates of biannual and monthly above-cloud aerosol (ACA) events globally. The active- (CALIOP) and passive-based (OMI-MODIS) techniques have their advantages and caveats for ACA detection, and thus both are used to derive a thorough and robust comparison of daytime cloudy-sky ACA distribution and climatology. For the first time, baseline above-cloud aerosol optical depth (ACAOD) and AI thresholds are derived and examined (AI  =  1.0, ACAOD  =  0.015) for each sensor. Both OMI-MODIS and CALIOP-based daytime spatial distributions of ACA events show similar patterns during both study periods (December–May) and (June–November). Divergence exists in some regions, however, such as Southeast Asia during June through November, where daytime cloudy-sky ACA frequencies of up to 10 % are found from CALIOP yet are non-existent from the OMI-based method. Conversely, annual cloudy-sky ACA frequencies of 20–30 % are reported over northern Africa from the OMI-based method yet are largely undetected by the CALIOP-based method. Using a collocated OMI-MODIS-CALIOP data set, our study suggests that the cloudy-sky ACA frequency differences between the OMI-MODIS- and CALIOP-based methods are mostly due to differences in cloud detection capability between MODIS and CALIOP as well as QA flags used. An increasing interannual variability of  ∼  0.3–0.4 % per year (since 2009) in global monthly cloudy-sky ACA daytime frequency of occurrence is found using the OMI-MODIS-based method. Yet, CALIOP-based global daytime ACA frequencies exhibit a near-zero interannual variability. Further analysis suggests that the OMI-derived interannual variability in cloudy-sky ACA frequency may be affected by OMI row anomalies in later years. A few regions are found to have increasing slopes in interannual variability in cloudy-sky ACA frequency, including the Middle East and India. Regions with slightly negative slopes of the interannual variability in cloudy-sky ACA frequencies are found over South America and China, while remaining regions in the study show nearly zero change in ACA frequencies over time. The interannual variability in ACA frequency is not, however, statistically significant on both global and regional scales, given the relatively limited sample sizes. A longer data record of ACA events is needed in order to establish significant trends of ACA frequency regionally and globally.

Capture–recapture estimates of space used in streams (CRESUS) at the population scale: case study on Zingel asper (percid), a threatened species of the Rhône catchment

2004 ◽  
Vol 61 (3) ◽  
pp. 476-486 ◽  
Author(s):  
Delphine Danancher ◽  
Jacques Labonne ◽  
Roger Pradel ◽  
Philippe Gaudin
Keyword(s):  
Spatial Data ◽  
Abiotic Factors ◽  
Estimation Method ◽  
Space Use ◽  
Longitudinal Axis ◽  
Spawning Period ◽  
Data Movement ◽  
Use Patterns ◽  
Capture Recapture ◽  
Population Scale

In this study, capture–mark–recapture statistics were applied to spatial recapture histories to assess the intensity of fish restricted movements along the longitudinal axis of a river using a previously described model for survival and recruitment analysis. Adapting the stopover estimation method to spatial data, movement probabilities were then used to estimate space used at the population scale. This capture–recapture estimates of space used in streams (CRESUS) method may thus be seen as a complementary tool of classic home range methods and should be used to explore the consequence of behavioural strategies on population mechanisms. We propose a methodological example where movements and space use strategies of a Zingel asper (percid) population in the Beaume River (Ardèche, France) were directly estimated at the population scale taking account of the effects of different biotic or abiotic factors. Results showed differences in Z. asper space use patterns among sexes, periods of biological cycle (growing and spawning period), and types of mesohabitat. Downstream movements were more important during the spawning period and by the way the riffle was more intensively used.

scholarly journals Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products

2018 ◽  
Vol 11 (1) ◽  
pp. 499-514 ◽  
Author(s):  
Travis D. Toth ◽  
James R. Campbell ◽  
Jeffrey S. Reid ◽  
Jason L. Tackett ◽  
Mark A. Vaughan ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Aerosol Optical Thickness ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Aerosol Extinction ◽  
Noise Floor ◽  
Data Products ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Level 2 ◽  
Global Mean

Abstract. Due to instrument sensitivities and algorithm detection limits, level 2 (L2) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm aerosol extinction profile retrievals are often populated with retrieval fill values (RFVs), which indicate the absence of detectable levels of aerosol within the profile. In this study, using 4 years (2007–2008 and 2010–2011) of CALIOP version 3 L2 aerosol data, the occurrence frequency of daytime CALIOP profiles containing all RFVs (all-RFV profiles) is studied. In the CALIOP data products, the aerosol optical thickness (AOT) of any all-RFV profile is reported as being zero, which may introduce a bias in CALIOP-based AOT climatologies. For this study, we derive revised estimates of AOT for all-RFV profiles using collocated Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT) and, where available, AErosol RObotic NEtwork (AERONET) data. Globally, all-RFV profiles comprise roughly 71 % of all daytime CALIOP L2 aerosol profiles (i.e., including completely attenuated profiles), accounting for nearly half (45 %) of all daytime cloud-free L2 aerosol profiles. The mean collocated MODIS DT (AERONET) 550 nm AOT is found to be near 0.06 (0.08) for CALIOP all-RFV profiles. We further estimate a global mean aerosol extinction profile, a so-called “noise floor”, for CALIOP all-RFV profiles. The global mean CALIOP AOT is then recomputed by replacing RFV values with the derived noise-floor values for both all-RFV and non-all-RFV profiles. This process yields an improvement in the agreement of CALIOP and MODIS over-ocean AOT.

scholarly journals MODIS Cloud Detection Evaluation Using CALIOP over Polluted Eastern China

Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 333 ◽  
Author(s):  
Saichun Tan ◽  
Xiao Zhang ◽  
Guangyu Shi
Keyword(s):  
Eastern China ◽  
Cloud Fraction ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Cloud Detection ◽  
Haze Pollution ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Cloud Optical Thickness ◽  
Moderate Resolution Imaging Spectroradiometer

Haze pollution has frequently occurred in winter over Eastern China in recent years. Over Eastern China, Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection data were compared with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) for three years (2013–2016) for three kinds of underlying surface types (dark, bright, and water). We found that MODIS and CALIOP agree most of the time (82% on average), but discrepancies occurred at low CALIOP cloud optical thickness (COT < 0.4) and low MODIS cloud top height (CTH < 1.5 km). In spring and summer, the CALIOP cloud fraction was higher by more than 0.1 than MODIS due to MODIS’s incapability of observing clouds with a lower COT. The discrepancy increased significantly with a decrease in MODIS CTH and an increase in aerosol optical depth (AOD, about 2–4 times), and MODIS observed more clouds that were undetected by CALIOP over PM2.5 > 75 μg m−3 regions in autumn and particularly in winter, suggesting that polluted weather over Eastern China may contaminate MODIS cloud detections because MODIS will misclassify a heavy aerosol layer as cloudy under intense haze conditions. Besides aerosols, the high solar zenith angle (SZA) in winter also affects MODIS cloud detection, and the ratio of MODIS cloud pixel numbers to CALIOP cloud-free pixel numbers at a high SZA increased a great deal (about 4–21 times) relative to that at low SZA for the three surfaces. As a result of the effects of aerosol and SZA, MODIS cloud fraction was 0.08 higher than CALIOP, and MODIS CTH was more than 2 km lower than CALIOP CTH in winter. As for the cloud phases and types, the results showed that most of the discrepancies could be attributed to water clouds and low clouds (cumulus and stratocumulus), which is consistent with most of the discrepancies at low MODIS CTH.

scholarly journals CALIPSO level 3 stratospheric aerosol profile product: version 1.00 algorithm description and initial assessment

2019 ◽  
Vol 12 (11) ◽  
pp. 6173-6191 ◽  
Author(s):  
Jayanta Kar ◽  
Kam-Pui Lee ◽  
Mark A. Vaughan ◽  
Jason L. Tackett ◽  
Charles R. Trepte ◽  
...  
Keyword(s):  
Space Station ◽  
Volcanic Eruptions ◽  
Satellite Observation ◽  
Stratospheric Aerosol ◽  
Initial Assessment ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Stratospheric Dynamics ◽  
Level 3 ◽  
Lidar Ratio

Abstract. In August 2018, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) project released a new level 3 stratospheric aerosol profile data product derived from nearly 12 years of measurements acquired by the spaceborne Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). This monthly averaged, gridded level 3 product is based on version 4 of the CALIOP level 1B and level 2 data products, which feature significantly improved calibration that now makes it possible to reliably retrieve profiles of stratospheric aerosol extinction and backscatter coefficients at 532 nm. This paper describes the science algorithm and data handling techniques that were developed to generate the CALIPSO version 1.00 level 3 stratospheric aerosol profile product. Further, we show that the extinction profiles (retrieved using a constant lidar ratio of 50 sr) capture the major stratospheric perturbations in both hemispheres over the last decade resulting from volcanic eruptions, extreme smoke events, and signatures of stratospheric dynamics. Initial assessment of the product by intercomparison with the stratospheric aerosol retrievals from the Stratospheric Aerosol and Gas Experiment III (SAGE III) on the International Space Station (ISS) indicates good agreement in the tropical stratospheric aerosol layer (30∘ N–30∘ S), where the average difference between zonal mean extinction profiles is typically less than 25 % between 20 and 30 km (CALIPSO biased high). However, differences can exceed 100 % in the very low aerosol loading regimes found above 25 km at higher latitudes. Similarly, there are large differences (≥100 %) within 2 to 3 km above the tropopause that might be due to cloud contamination issues.

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