Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the summer 2017 OWLETS campaign

Dacic, Natasha; Sullivan, John T.; Knowland, K. Emma; Wolfe, G. M.; Oman, Luke D.; Berkoff, Timothy A.; Gronoff, Guillaume

doi:10.1016/j.atmosenv.2019.117133

Cited by 24 publications

(23 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…GEOS-CF offers a new tool for academic researchers, air quality managers, and the public. Applications include flight campaign planning, support of satellite and other remote-sensing observations, interpretation of field campaign data (Dacic et al, 2020;Johnson et al, 2021), and air quality research (Keller et al, 2020). OMI-HTAP (Liu et al, 2018) Global except Africa Anthropogenic VOCs RETRO (Schultz et al, 2008) Global except Africa Anthropogenic NO, CO, SO2, BC, OC, NH3, VOCs DICE-Africa (Marais and Wiedinmyer, 2016) Africa Arctic seabird NH3…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…The model generally overestimates surface O3 over Europe, North and South America and Australia by 5-10 ppbv and underestimates it over Africa and Asia by up to 20 ppbv. The model-observation mismatch is larger than for the remote GAW sites, suggesting that sub-grid factors such as vertical and horizontal model representation errors and nighttime loss of O3 by reaction with NO contribute to this difference (Travis et al, 2019;Dacic et al, 2020). Global models tend to underestimate O3 nighttime depletion due to difficulties to resolve small-scale horizontal NO2 gradients, and evaluation of surface O3 is thus often restricted to daytime or afternoon O3 (Millet et al, 2015;Hu et al, 2018;Travis et al, 2019).…”

Section: Accepted Articlementioning

confidence: 99%

See 2 more Smart Citations

Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0

Keller

Knowland

Duncan

et al. 2021

J Adv Model Earth Syst

Self Cite

101

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Accepted Articlementioning

confidence: 99%

See 1 more Smart Citation

Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0

Keller

Knowland

Duncan

et al. 2021

J Adv Model Earth Syst

Self Cite

101

View full text Add to dashboard Cite

show abstract

“…For LMOL data products, the vertical resolution (110 m to 990m) of the O3 profiles varies with altitude to preserve a retrieval uncertainty within ±10%, the uncertainty of which is calculated using poison statistics of the backscattered photons. LMOL has been used in several campaigns such as Ozone Water-Land Environmental Transition Study (OWLETS) I and II, LISTOS (Berkoff et al,2018;Sullivan et al, 2019;Dacic et al, 2020), Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ), and Southern California Ozone Observation Project (SCOOP) (Leblanc et al, 2018). In the context of LISTOS (Wu et al, 2021), and more specifically for the present study, LMOL was deployed at Sherwood Island Park, Westport, CT (41.1182° N, 73.3368° W, 2.5 m ASL) and obtained measurements between July 12 and August 29, 2018.…”

Section: The Lmol Systemmentioning

confidence: 99%

Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system

Lei

Berkoff

Gronoff

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Aerosols emitted from wildfires are becoming one of the main sources of poor air quality in the US mainland. Their extinction in UVB (wavelength range 280–315 nm) is difficult to be retrieved using simple lidar techniques because of the impact of O3 absorption and lacking information of lidar ratio at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) campaign in the New York City region allowed the characterization of lidar ratio for UVB aerosol retrieval. An algorithm for the aerosol extinction retrieval out of the Langley Mobile Ozone Lidar (LMOL) was used in conjunction with the NASA Langley High Altitude Lidar Observatory (HALO) 532 nm aerosol extinction product. This approach requires assuming 2 parameters, the lidar ratio at 292 nm and the Ångström Exponent (AE) between 532 nm and 292 nm. The objective of this work is to determine these two parameters and assess the retrieval error caused by improper assumption of lidar ratio. This work also accomplishes the first know 292 nm aerosol product inter-comparison between HALO and Tropospheric Ozone Lidar Network (TOLNet) ozone lidar. HALO results were compared with the aerosol data retrieved from the 292 nm band from LMOL with different approximations of the lidar ratio and the AE to determine optimal parameters. Using optimized parameters, the LMOL aerosol extinction can be retrieved with a 10 % accuracy up to 3 km. This work highlights the importance of the lidar ratio and AE in the retrieval and validation of 292 nm aerosol profiles obtained from UV-lidar. Errors arise from approaches that utilize a random priori lidar ratio and AE assumption. The lidar ratios at 292 nm determined in this work will also improve our understanding of the UVB optical properties of aerosol in the lower troposphere affected by transported wildfire emission.

show abstract

“…The high temporal resolution characteristic will greatly reduce the underestimation degree of HALF, but this underestimation cannot be avoided. Assimilating a variety of aerosol datasets from different remote sensing platforms (MODIS, MISR, AERONET), the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) was generated by the NASA Global Modeling-Assimilation Office (GMAO) [29][30][31]. The latest MERRA-2 dataset contains global aerosol characteristics on an hourly scale, which provides great support for the precise acquisition of regional HALF [32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets

Huang

Sun

et al. 2021

Remote Sensing

View full text Add to dashboard Cite

Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols.

show abstract

Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the summer 2017 OWLETS campaign

Cited by 24 publications

References 49 publications

Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0

Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0

Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system

Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets

Contact Info

Product

Resources

About