Application of CALIOP Measurements to the Evaluation of Cloud Phase Derived from MODIS Infrared Channels

Abstract In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) infrared-based cloud thermodynamic phase retrievals are evaluated using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals for the 6 months from January to June of 2008. The CALIOP 5-km cloud-layer product provides information on cloud opacity, cloud-top height, midlayer cloud temperature, and cloud thermodynamic phase. Comparisons are made between MODIS IR phase and CALIOP observations for single-layer clouds (54% of the cloudy CALIOP scenes) and for the top layer of the CALIOP scenes. Both CALIOP and MODIS retrieve larger fractions of water clouds in the single-layer cases than in the top-layer cases, demonstrating that focusing on only single-layer clouds may introduce a water-cloud bias. Of the single-layer clouds, 60% are transparent and 40% are opaque (defined by the lack of a CALIOP ground return). MODIS tends to classify single-layer clouds with midlayer temperatures below −40°C as ice; around −30°C nearly equally as ice, mixed, and unknown; between −28° and −15°C as mixed; and above 0°C as water. Ninety-five percent of the single-layer CALIOP clouds not detected by MODIS are transparent. Approximately ⅓ of transparent single-layer clouds with temperatures below −30°C are not detected by MODIS and close to another ⅓ are classified as ice, with the rest assigned as water, mixed, or unknown. CALIOP classes nearly all of these transparent cold clouds as ice.

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-47-2016 ◽

2016 ◽

Vol 16 (1) ◽

pp. 47-69 ◽

Cited By ~ 13

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.

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MODIS Cloud Detection Evaluation Using CALIOP over Polluted Eastern China

Atmosphere ◽

10.3390/atmos10060333 ◽

2019 ◽

Vol 10 (6) ◽

pp. 333 ◽

Cited By ~ 3

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.

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Derivation of Shortwave Radiometric Adjustments for SNPP and NOAA-20 VIIRS for the NASA MODIS-VIIRS Continuity Cloud Products

Remote Sensing ◽

10.3390/rs12244096 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4096 ◽

Cited By ~ 2

Author(s):

Kerry Meyer ◽

Steven Platnick ◽

Robert Holz ◽

Steve Dutcher ◽

Greg Quinn ◽

...

Keyword(s):

Optical Properties ◽

Infrared Imaging ◽

Trend Detection ◽

Adjustment Factors ◽

Moderate Resolution ◽

Resolution Imaging ◽

Water Cloud ◽

Moderate Resolution Imaging Spectroradiometer ◽

New Generation ◽

Cloud Mask

Climate studies, including trend detection and other time series analyses, necessarily require stable, well-characterized and long-term data records. For satellite-based geophysical retrieval datasets, such data records often involve merging the observational records of multiple similar, though not identical, instruments. The National Aeronautics and Space Administration (NASA) cloud mask (CLDMSK) and cloud-top and optical properties (CLDPROP) products are designed to bridge the observational records of the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard NASA’s Aqua satellite and the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the joint NASA/National Oceanic and Atmospheric Administration (NOAA) Suomi National Polar-orbiting Partnership (SNPP) satellite and NOAA’s new generation of operational polar-orbiting weather platforms (NOAA-20+). Early implementations of the CLDPROP algorithms on Aqua MODIS and SNPP VIIRS suffered from large intersensor biases in cloud optical properties that were traced back to relative radiometric inconsistency in analogous shortwave channels on both imagers, with VIIRS generally observing brighter top-of-atmosphere spectral reflectance than MODIS (e.g., up to 5% brighter in the 0.67 µm channel). Radiometric adjustment factors for the SNPP and NOAA-20 VIIRS shortwave channels used in the cloud optical property retrievals are derived from an extensive analysis of the overlapping observational records with Aqua MODIS, specifically for homogenous maritime liquid water cloud scenes for which the viewing/solar geometry of MODIS and VIIRS match. Application of these adjustment factors to the VIIRS L1B prior to ingestion into the CLDMSK and CLDPROP algorithms yields improved intersensor agreement, particularly for cloud optical properties.

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Investigating the frequency and trends in global above-cloud aerosol characteristics with CALIOP and OMI

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-4173-2015 ◽

2015 ◽

Vol 15 (4) ◽

pp. 4173-4217 ◽

Cited By ~ 1

Author(s):

R. Alfaro-Contreras ◽

J. Zhang ◽

J. R. Campbell ◽

J. S. Reid

Keyword(s):

Orthogonal Polarization ◽

Ozone Monitoring Instrument ◽

Regional Trends ◽

Data Record ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Increasing Trends ◽

First Time ◽

Aerosol Index

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.

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The Continuity MODIS-VIIRS Cloud Mask

Remote Sensing ◽

10.3390/rs12203334 ◽

2020 ◽

Vol 12 (20) ◽

pp. 3334 ◽

Cited By ~ 3

Author(s):

Richard A. Frey ◽

Steven A. Ackerman ◽

Robert E. Holz ◽

Steven Dutcher ◽

Zach Griffith

Keyword(s):

Infrared Imaging ◽

Cloud Fraction ◽

The Arctic ◽

Orthogonal Polarization ◽

Cloud Detection ◽

Moderate Resolution ◽

Resolution Imaging ◽

Hit Rates ◽

Moderate Resolution Imaging Spectroradiometer ◽

Cloud Mask

This paper introduces the Continuity Moderate Resolution Imaging Spectroradiometer (MODIS)-Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (MVCM), a cloud detection algorithm designed to facilitate continuity in cloud detection between the MODIS (Moderate Resolution Imaging Spectroradiometer) on the Aqua and Terra platforms and the series of VIIRS (Visible Infrared Imaging Radiometer Suite) instruments, beginning with the Soumi National Polar-orbiting Partnership (SNPP) spacecraft. It is based on the MODIS cloud mask that has been operating since 2000 with the launch of the Terra spacecraft (MOD35) and continuing in 2002 with Aqua (MYD35). The MVCM makes use of fourteen spectral bands that are common to both MODIS and VIIRS so as to create consistent cloud detection between the two instruments and across the years 2000–2020 and beyond. Through comparison data sets, including collocated Aqua MODIS and Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) from the A-Train, this study was designed to assign statistical consistency benchmarks between the MYD35 and MVCM cloud masks. It is shown that the MVCM produces consistent cloud detection results between Aqua MODIS, SNPP VIIRS, and NOAA-20 VIIRS and that the quality is comparable to the standard Aqua MODIS cloud mask. Globally, comparisons with collocated CALIOP lidar show combined clear and cloudy sky hit rates of 88.2%, 87.5%, 86.8%, and 86.8% for MYD35, MVCM Aqua MODIS, MVCM SNPP VIIRS, and MVCM NOAA-20 VIIRS, respectively, for June through until August, 2018. For the same months and in the same order for 60S–60N, hit rates are 90.7%, 90.5%, 90.1%, and 90.3%. From the time series constructed from gridded daily means of 60S–60N cloud fractions, we found that the mean day-to-day cloud fraction differences/standard deviations in percent to be 0.68/0.55, 0.94/0.64, −0.20/0.50, and 0.44/0.82 for MVCM Aqua MODIS-MVCM SNPP VIIRS day and night, and MVCM NOAA-20 VIIRS-MVCM SNPP VIIRS day and night, respectively. It is seen that the MODIS and VIIRS 1.38 µm cirrus detection bands perform similarly but with MODIS detecting slightly more clouds in the middle to high levels of the troposphere and the VIIRS detecting more in the upper troposphere above 16 km. In the Arctic, MVCM Aqua MODIS and SNPP VIIRS reported cloud fraction differences of 0–3% during the mid-summer season and −3–4% during the mid-winter.

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Satellite Observations of Cloud-Related Variations in Aerosol Properties

Atmosphere ◽

10.3390/atmos9110430 ◽

2018 ◽

Vol 9 (11) ◽

pp. 430 ◽

Cited By ~ 6

Author(s):

Tamás Várnai ◽

Alexander Marshak

Keyword(s):

Particle Size ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Cloud Amount ◽

Orthogonal Polarization ◽

Radiative Processes ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Aerosol Properties

This paper presents an overview of our efforts to characterize and better understand cloud-related changes in aerosol properties. These efforts primarily involved the statistical analysis of global or regional datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol and cloud observations. The results show that in oceanic regions, more than half of all aerosol measurements by passive satellite instruments come from near-cloud areas, where clouds and cloud-related processes may significantly modify aerosol optical depth and particle size. Aerosol optical depth is also shown to increase systematically with regional cloud amount throughout the Earth. In contrast, it is shown that effective particle size can either increase or decrease with increasing cloud cover. In bimodal aerosol populations, the sign of changes depends on whether coarse mode or small mode aerosols are most affected by clouds. The results also indicate that over large parts of Earth, undetected cloud particles are not the dominant reason for the satellite-observed changes with cloud amount, and that 3D radiative processes contribute about 30% of the observed near-cloud changes. The findings underline the need for improving our ability to accurately measure aerosols near clouds.

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Construction of Nighttime Cloud Layer Height and Classification of Cloud Types

Remote Sensing ◽

10.3390/rs12040668 ◽

2020 ◽

Vol 12 (4) ◽

pp. 668 ◽

Cited By ~ 1

Author(s):

Sijie Chen ◽

Chonghui Cheng ◽

Xingying Zhang ◽

Lin Su ◽

Bowen Tong ◽

...

Keyword(s):

Dead Zone ◽

Cloud Layer ◽

Spectral Radiance ◽

Cloud Base ◽

Track Reconstruction ◽

Cloud Structure ◽

Ground Track ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

A cloud structure construction algorithm adapted for the nighttime condition is proposed and evaluated. The algorithm expands the vertical information inferred from spaceborne radar and lidar via matching of infrared (IR) radiances and other properties at off-nadir locations with their counterparts that are collocated with active footprints. This nighttime spectral radiance matching (NSRM) method is tested using measurements from CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Moderate Resolution Imaging Spectroradiometer (MODIS). Cloud layer heights are estimated up to 400 km on both sides of the ground track and reconstructed with the dead zone setting for an approximate evaluation of the reliability. By mimicking off-nadir pixels with a dead zone around pixels along the ground track, reconstruction of nadir profiles shows that, at 200 km from the ground track, the cloud top height (CTH) and the cloud base height (CBH) reconstructed by the NSRM method are within 1.49 km and 1.81 km of the original measurements, respectively. The constructed cloud structure is utilized for cloud classification in the nighttime. The same method is applied to the daytime measurements for comparison with collocated MODIS classification based on the International Satellite Cloud Climatology Project (ISCCP) standard. The comparison of eight cloud types over the expanded distance shows good agreement in general.

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Calibration of global MODIS cloud amount using CALIOP cloud profiles

10.5194/amt-2020-111 ◽

2020 ◽

Author(s):

Andrzej Z. Kotarba

Keyword(s):

Cloud Amount ◽

Satellite Observation ◽

Cloud Fraction ◽

Orthogonal Polarization ◽

Polar Regions ◽

Cloud Detection ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Cloud Mask

Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection procedure classifies instantaneous fields of view (IFOV) as either confident cloudy, probably cloudy, probably clear, or confident clear. The cloud amount calculation requires quantitative cloud fractions to be assigned to these classes. The operational procedure used by NASA assumes that confident clear and probably clear IFOV are cloud-free (cloud fraction 0 %), while the remaining categories are completely filled with clouds (cloud fraction 100 %). This study demonstrates that this best guess approach is unreliable, especially on a regional/ local scale. We use data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument flown on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, collocated with MODIS/ Aqua IFOV. Based on 33,793,648 paired observations acquired in January and July 2015, we conclude that actual cloud fractions to be associated with MODIS cloud mask categories are 21.5 %, 27.7 %, 66.6 %, and 94.7 %. Spatial variability is significant, even within a single MODIS algorithm path, and the operational approach introduces uncertainties of up to 30 % of cloud amount, notably in the polar regions at night, and in selected locations over the northern hemisphere. Applications of MODIS data at ~10 degrees resolution (or finer) should first assess the extent of the error. Uncertainties were related to the efficiency of the cloud masking algorithm. Until the algorithm can be significantly modified, our method is a robust way to calibrate (correct) MODIS estimates. It can be also used for MODIS/ Terra data, and other missions where the footprint is collocated with CALIPSO.

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CALIOP V4 Cloud Thermodynamic Phase Assignment and the Impact of Near-Nadir Viewing Angles

10.5194/amt-2019-388 ◽

2020 ◽

Cited By ~ 1

Author(s):

Melody A. Avery ◽

Robert A. Ryan ◽

Brian J. Getzewich ◽

Mark A. Vaughan ◽

David M. Winker ◽

...

Keyword(s):

Specular Reflection ◽

Accurate Determination ◽

Cloud Layer ◽

Orthogonal Polarization ◽

Viewing Angle ◽

Ice Clouds ◽

Water Cloud ◽

Thermodynamic Phase ◽

The Impact ◽

532 Nm

Abstract. Accurate determination of thermodynamic cloud phase is critical for establishing the radiative impact of clouds on climate and weather. Depolarization of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm signal provides an independent piece of information for determining cloud phase, a critical addition to other methods of thermodynamic phase discrimination that rely on temperature, cloud top altitude or a temperature-based cloud phase climatology. The CALIOP phase algorithm primarily uses layer-integrated depolarization and attenuated backscatter to determine the dominant thermodynamic phase of hydrometeors present in a vertical cloud layer segment, at horizontal resolutions varying between 333 m and 80 km. Ice cloud backscatter observations taken with a 0.3° near-nadir view include a significant amount of specular reflection from hexagonal smooth crystal faces that are oriented perpendicularly to the incident lidar beam. These specular reflections are often caused by horizontally oriented ice crystals (HOI), and are shown to occur between 0 and −40° C, with a peak in the distribution globally at −15° C. To avoid these reflections, the viewing angle was changed from 0.3 to 3° in November 2007. Since then the instrument has been observing clouds almost continuously for almost 12 more years. Recent viewing angle testing occurring during 2017 at 1, 1.5 and 2° quantifies the impact of changing the viewing angle to CALIOP global observations of attenuated backscatter and depolarization. These CALIOP results verify earlier observations by POLDER, showing that at the peak of the HOI distribution the mean backscatter from ice clouds decreases by 50 % and depolarization increases by a factor of 5 as the viewing angle increases from 0.3 to 3°. This has provided more data for a thorough evaluation of phase determination at the 3° viewing angle and suggested changes to the CALIOP cloud phase algorithm for Version 4 (V4). Combined with extensive calibration changes that impact the 532 nm and 1064 nm backscatter observations, V4 represents the first major Level 2 phase algorithm adjustment since 2009. For V4 the algorithm has been simplified to exclude over-identification of HOI at 3°, particularly in cold clouds. The V4 algorithm also considers temperature at the 532 nm cloud layer centroid, as opposed to cloud top or mid-cloud temperature as a secondary means of determining cloud phase and has been streamlined for more consistent identification of water and ice clouds. In this paper we summarize the major Version 3 (V3) to V4 cloud phase algorithm changes. We also characterize the impacts of applying the V4 phase algorithm globally and describe changes that can be expected when comparing V4 with V3. In V4 there are more cloud layers detected in V4, with edges that may extend further than in V3, for a combined increase in total atmospheric cloud volume of 6–9 % for high confidence cloud phases and 1–2 % for all cloudy bins. Some cloud layer boundaries have changed because 532 nm layer-integrated attenuated backscatter in V4 has increased due to improved calibration and extended layer boundaries, while the corresponding depolarization has stayed about the same. Collocated CALIPSO Imaging Infrared Radiometer (IIR) observations of ice and water cloud particle microphysical indices complement the CALIOP ice and water cloud phase determinations.

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Impact of data quality and surface-to-column representativeness on the PM<sub>2.5</sub>/satellite AOD relationship for the Continental United States

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-31635-2013 ◽

2013 ◽

Vol 13 (12) ◽

pp. 31635-31671 ◽

Cited By ~ 5

Author(s):

T. D. Toth ◽

J. Zhang ◽

J. R. Campbell ◽

E. J. Hyer ◽

J. S. Reid ◽

...

Keyword(s):

United States ◽

Data Quality ◽

Dry Mass ◽

Orthogonal Polarization ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Total Column ◽

Particle Mass Concentration

Abstract. Satellite-derived aerosol optical depth (AOD) observations have been used to estimate particulate matter less than 2.5 μm (PM2.5). However, such a relationship could be affected by the representativeness of satellite-derived AOD to surface aerosol particle mass concentration and satellite AOD data quality. Using purely measurement-based methods, we have explored the impacts of data quality and representativeness on the AOD inferred PM2.5/AOD relationship for the Continental United States (CONUS). This is done through temporally and spatially collocated datasets of PM2.5 and AOD retrievals from Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). These analyses show that improving data quality of satellite AOD, such as done with data assimilation-grade retrievals, increases their correlation with PM2.5. However, overall correlation is relatively low across the CONUS. Also, integrated extinction observed within the 500 m above groud level (a.g.l.), as measured by CALIOP, is not well representative of the total column AOD. Surface aerosol in the Eastern CONUS is better correlated than in the Western CONUS. The best correlation values are found for estimated dry mass CALIOP extinction at 200–300 m a.g.l. and PM2.5, but additional work is needed to address the ability of using actively sensed AOD as a proxy for PM2.5 concentrations.

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