scholarly journals Long-Term Analyses of Aerosol Optical Thickness Using Caliop

2020 ◽  
Vol 237 ◽  
pp. 02023
Author(s):  
Masahiro Fujikawa ◽  
Rei Kudo ◽  
Tomoaki Nishizawa ◽  
Eiji Oikawa ◽  
Akiko Higurashi ◽  
...  

We developed an algorithm to derive extinction coefficients for four aerosol components (water-soluble, dust, sea salt, black carbon) from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. The algorithm was applied to the nine-year data for 2007–2015 and the results were compared to CALIOP standard product (CALIOP-ST) and MODerate resolution Imaging Spectroradiometer (MODIS) standard product (MODIS-ST). Comparisons of the total aerosol optical thickness (AOT) showed that MODIS-ST was the largest, followed by CALIOP-ST (Ver.4), and our product. CALIOP-ST (Ver.3) showed a similar magnitude to ours.

2018 ◽  
Author(s):  
Sarah A. Strode ◽  
Junhua Liu ◽  
Leslie Lait ◽  
Róisín Commane ◽  
Bruce Daube ◽  
...  

Abstract. GEOS-5 forecasts and analyses show considerable skill in predicting and simulating the CO distribution and the timing of CO enhancements observed during the ATom-1 aircraft mission. Using tagged tracers for CO, we find a dominant contribution from non-biomass burning sources along the ATom transects except over the tropical Atlantic, where African biomass burning makes a large contribution to the CO concentration. One of the goals of ATom is to provide a chemical climatology over the oceans, so it is important to consider whether August 2016 was representative of typical summer conditions. Using satellite observations of 700 hPa and column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument, 215 hPa CO from the Microwave Limb Sounder (MLS), and aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS), we find that CO concentrations and aerosol optical thickness in August 2016 were within the observed range of the satellite observations, but below the decadal median for many of the regions sampled. This suggests that the ATom-1 measurements may represent relatively clean but not exceptional conditions for lower tropospheric CO.


2012 ◽  
Vol 5 (2) ◽  
pp. 2795-2820 ◽  
Author(s):  
P. R. Colarco ◽  
L. A. Remer ◽  
R. A. Kahn ◽  
R. C. Levy ◽  
E. J. Welton

Abstract. We assess the impact of swath width on the statistics of aerosol optical thickness (AOT) retrieved by satellite, as inferred from observations made by the Moderate Resolution Imaging Spectroradiometer (MODIS). Using collocated AERONET sun photometer observations we develop a correction to the MODIS data to account for calibration and algorithmic view angle dependency in the retrieved AOT. We sub-sample and correct the AOT data from the MODIS Aqua instrument along several candidate swaths of various widths for the years 2003–2011. We find that over ocean the global, annual mean AOT is within ± 0.01 of the full swath AOT for all of our sub-samples. Over land, however, most of our sub-samples are outside of this criterion range in the global, annual mean. Moreover, at smaller spatial and temporal scales we find wide deviation in the sub-sample AOT relative to the full swath over both land and ocean. In all, the sub-sample AOT is within ± 0.01 of the full swath value less than 25% of the time over land, and less than 50% of the time over ocean (less than 35% for all but the widest of our sub-sample swaths). These results suggest that future aerosol satellite missions having only narrow swath views may not sample the true AOT distribution sufficiently to reduce significantly the uncertainty in aerosol direct forcing of climate.


2015 ◽  
Vol 18 (1) ◽  
pp. 1-20
Author(s):  
Noelia Rojas Benavente ◽  
Joel Rojas Acuña

El objetivo de este trabajo es estudiar la dinámica de los aerosoles en el Perú y América del Sur entre las latitudes 4°N-24°S y las longitudes 83°W-33°W, a partir de las imágenes de los promedios mensuales del espesor óptico de los aerosoles, Aerosol Optical Thickness, AOT, en la longitud de onda de 550 nm medidos por el sensor MODIS, Moderate Resolution Imaging Spectroradiometer, a bordo de los satélites TERRA y AQUA, para un periodo de catorce años, del 2000 al 2013. Se han usado los datos AOT in-situ en los horarios de 6 estaciones AERONET de América del Sur que incluyen cuatro de Brasil, tales como, Rio Branco, Paraná Ji, Alta Foresta y Campo Grande; uno de Chile, la estación de Arica y uno de Bolivia, la estación de La Paz; además incorporamos 166 datos imágenes AOT-MODIS-TERRA de los productos mensuales obtenidos para un periodo del 2000 al 2013 y 138 datos imágenes AOT-MODIS-AQUA de los productos mensuales obtenidos para un periodo del 2002 al 2013 estimados a partir de la herramienta de visulaización y análisis vía Web Giovanni con una resolución de 1°×1°, es decir, de 110 km×110 km. La serie de tiempos AOT-MODIS-TERRA tienen valores máximos y mínimos entre 0.0 y 0.499 y sus valores máximos se ubican en la temporada seca del Hemisferio Sur, entre agosto a noviembre, durante los 14 años. La serie de tiempos AOT-MODIS-AQUA tienen valores máximos y mínimos entre 0.0 y 0.493 y sus valores máximos se ubican en la temporada seca, durante los 12 años. La serie de tiempos AOT-AERONET en las cuatro estaciones de Brasil muestra una variación estacional con máximos en la estación seca durante los 14 años, mientras que, en las estaciones de Chile y Bolivia se muestra una variación estacional muy diferente a los datos AOT/MODIS, teniendo pocos registros de datos AOT. Las gráficas de dispersión de las series de tiempo AOT-MODIS vs AOT-AERONET muestran una alta correlación de 0.8 a 0.9 en cuatro estaciones de Brasil y una correlación baja de 0.33 a 0.39 en la estación de Chile y de 0.13 a 0.19 en la estación de Bolivia.


2016 ◽  
Vol 16 (1) ◽  
pp. 47-69 ◽  
Author(s):  
R. Alfaro-Contreras ◽  
J. Zhang ◽  
J. R. Campbell ◽  
J. S. Reid

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.


2018 ◽  
Vol 11 (1) ◽  
pp. 499-514 ◽  
Author(s):  
Travis D. Toth ◽  
James R. Campbell ◽  
Jeffrey S. Reid ◽  
Jason L. Tackett ◽  
Mark A. Vaughan ◽  
...  

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.


Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 333 ◽  
Author(s):  
Saichun Tan ◽  
Xiao Zhang ◽  
Guangyu Shi

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.


2004 ◽  
Vol 39 ◽  
pp. 223-230 ◽  
Author(s):  
Ian C. Brown ◽  
Ted A. Scambos

AbstractWe use satellite images to track seasonal and interannual variations in blue-ice extent over the past 30 years near Byrd Glacier on the East Antarctic plateau. The study areas have low slope and few nearby nunataks, which may increase their climate sensitivity. A threshold-based algorithm sensitive to snow grain-size is used to analyze 56 Moderate Resolution Imaging Spectroradiometer (MODIS) images over three recent summer seasons. Seasonal blue-ice exposure grows rapidly in late spring, and peaks by late December. Exposure is relatively constant between late December and mid-January, then declines in February. We interpret this cycle as due to removal and re-accumulation of patchy snow. Interannual changes in blue-ice area may be estimated by tracking the near-constant summer maximum extent period. Fifteen mid-summer Landsat images, spanning 1974–2002, were analyzed to determine long-term variations. Interannual area changes are 10–30%; however, the MODIS data revealed that the exposed blue-ice area can be sharply reduced for up to 2 weeks after a snowfall event; and in the 2001/02 season, patchy snow cover persisted for the entire summer. The combination of MODIS seasonal and Landsat interannual data indicates that blue-ice areas can be climate-sensitive. The strong feedback between snow cover and surface energy balance implies that blue-ice areas could rapidly decrease due to climate-related increases in snowfall or reduced ablation.


2015 ◽  
Vol 15 (4) ◽  
pp. 4173-4217 ◽  
Author(s):  
R. Alfaro-Contreras ◽  
J. Zhang ◽  
J. R. Campbell ◽  
J. S. Reid

Abstract. Seven and a half years (June 2006–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, to investigate variability in estimates of bi-annual 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 get 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. This is possibly due to a misclassification of thick dust plumes as clouds by the OMI-MODIS based method. An increasing trend of ~0.5% 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 trend. Further analysis suggests that the OMI derived cloudy-sky ACA frequency trend may be affected by OMI row anomalies in later years. A few regions are found to have increasing trends of cloudy-sky ACA frequency, including the Middle-East and India. Regions with slightly negative cloudy-sky ACA frequency trends are found over South America and the Southern Oceans, while remaining regions in the study show a near-zero trend. Global and regional trends are not statistically significant, though, given relatively lacking sample sizes. A longer data record of ACA events is needed in order to establish a more significant trend of ACA frequency regionally and globally.


2012 ◽  
Vol 25 (13) ◽  
pp. 4699-4720 ◽  
Author(s):  
Robert Pincus ◽  
Steven Platnick ◽  
Steven A. Ackerman ◽  
Richard S. Hemler ◽  
Robert J. Patrick Hofmann

Abstract The properties of clouds that may be observed by satellite instruments, such as optical thickness and cloud-top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through “instrument simulators,” diagnostic tools that map the model representation to synthetic observations so that differences can be interpreted as model error. But simulators may themselves be restricted by limited information or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Satellite Cloud Climatology Project (ISCCP), two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail datasets developed for comparison with global models using ISCCP and MODIS simulators. In nature MODIS observes less midlevel cloudiness than ISCCP, consistent with the different methods used to determine cloud-top pressure; aspects of this difference are reproduced by the simulators. Differences in observed distributions of optical thickness, however, are not captured. The largest differences can be traced to different approaches to partly cloudy pixels, which MODIS excludes and ISCCP treats as homogeneous. These cover roughly 15% of the planet and account for most of the optically thinnest clouds. Instrument simulators cannot reproduce these differences because there is no way to synthesize partly cloudy pixels. Nonetheless, MODIS and ISCCP observations are consistent for all but the optically thinnest clouds, and models can be robustly evaluated using instrument simulators by integrating over the robust subset of observations.


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