Publications

@article{Arnold2025,

title = {Constraints on the modeled vertical distribution of smoke during the 2020 western US wildfires from satellite data},

author = {Mackenzie M. Arnold and Pablo E. Saide and Kazuyuki Miyazaki and Kevin W. Bowman and Jordan L. Schnell and Ravan Ahmadov and Xi Chen and Jun Wang and Oscar A. Neyra-Nazarrett},

url = {https://doi.org/10.1038/s44407-025-00036-3},

doi = {10.1038/s44407-025-00036-3},

issn = {3059-2240},

year  = {2025},

date = {2025-12-04},

journal = {npj Clean Air},

volume = {1},

number = {1},

pages = {37},

abstract = {As wildfires increase in frequency and intensity, accurately representing the vertical distribution of smoke in numerical models is critical for assessing impacts to air quality, but remains highly uncertain. In this study, we leverage satellite retrievals of total column carbon monoxide (CO) and aerosol layer height (ALH) to evaluate two state-of-the-art regionals and global models, one using a plume rise parameterization to estimate smoke injection height (RAP-Chem) and another placing smoke at the surface (MOMO-Chem). We introduce a novel metric that utilizes the differing vertical sensitivities of two satellite sensors observing CO (TROPOMI and CrIS) to infer the vertical distribution of wildfire smoke using a joint CO column ratio. We find that RAP-Chem better captures the distribution of CO and ALH related to the 2020 western US megafire event than MOMO-Chem. However, RAP-Chem underestimates surface CO concentrations, revealing that current plume rise parameterizations are limited in their ability to partition smoke correctly in the vertical column. These results show that synergistic use of satellite data can provide additional constraints on the vertical distribution of smoke, thus providing insights into the strengths and limitations of current plume rise parameterizations and a pathway to improvement.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2025JD044477,

title = {Aerosol Fine Mode Fraction Retrievals for the Marine Boundary Layer From Airborne Lidar},

author = {Pablo E. Saide and Julianna Christopoulos and Richard A. Ferrare and Johnathan W. Hair and Taylor Shingler and Marta A. Fenn and Amy Jo Scarino and Sharon P. Burton and Amin R. Nehrir and Rory A. Barton-Grimley and Brian L. Collister and Richard H. Moore and Luke D. Ziemba and Michael A. Shook and Joseph Schlosser and Ewan Crosbie and Christiane Voigt and Simon Kirschler and Joshua P. DiGangi and Glenn S. Diskin and Armin Sorooshian},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2025JD044477},

doi = {https://doi.org/10.1029/2025JD044477},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {130},

number = {20},

pages = {e2025JD044477},

abstract = {Abstract Separating contributions of the fine and coarse modes is important for characterizing aerosols and assessing their impacts. This work develops retrievals of fine mode fraction (FMF) from lidar observables for the marine boundary layer (MBL) using data collected during the ACTIVATE field campaign. First, we calculate multiwavelength backscatter and extinction and derived metrics for spherical particles derived from measured size distributions (combining in situ aerosol and cloud probes) and hygroscopicity estimates. The calculations show reasonable skill when compared to airborne High Spectral Resolution Lidar—generation 2 (HSRL-2) retrievals, displaying low biases and explaining up to 87% of the variability in backscattering. While slopes are generally close to 1:1 for lidar ratios and Angstrom exponents (AEs), the variability within HSRL-2 data is only well captured for lidar ratios (50%–67%). Having established that the calculated optical properties are representative of remotely sensed ones in the marine environment, they are used together with in situ aircraft particle size data to train multilinear regression models to estimate FMF proxies (extinction FMF, PM1/PM10 and PM2.5/PM10 ratios). When tested with HSRL-2 observations as inputs, these models can represent up to 67%–78% of the variability of the observed FMF proxies with biases at high FMFs that depend on the accuracy of the coarse mode aerosol size measurements. The regression retrievals are tested for lidar transects and show expected gradients due to continental influence on the MBL and differential hygroscopicity of fine versus coarse mode aerosol with height. These results are encouraging for their application for various lidar systems.},

note = {e2025JD044477 2025JD044477},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2024JD042538,

title = {Improving Planetary Boundary Layer Height Estimation From Airborne Lidar Instruments},

author = {J. A. Christopoulos and P. E. Saide and R. Ferrare and B. Collister and R. A. Barton-Grimley and A. J. Scarino and J. Collins and J. W. Hair and A. Nehrir},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024JD042538},

doi = {https://doi.org/10.1029/2024JD042538},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {130},

number = {9},

pages = {e2024JD042538},

abstract = {Abstract The height of the planetary boundary layer (PBLH) influences processes such as pollutant distributions, convection, and cloud formation within the troposphere. Aerosol observables play a critical role in deriving the mixed layer height (MLH) using retrieval techniques like the Haar wavelet covariance transform (WCT), which employs gradients in aerosol backscatter to estimate MLH. Currently, backscatter-only approaches struggle with identifying very shallow stable boundary layers, distinguishing PBL from lofted residual or other aerosol layers, and profiles with very low aerosol loading. Here, we reflect on the WCT method's performance and evaluate different approaches to improve PBLH estimations. We aggregate lidar observables from recent NASA airborne field campaigns and compute MLHs based on the WCT method. Machine learning (ML) approaches are explored to produce PBLH estimates by training lidar information on thermodynamically derived PBLHs over marine and land settings. A linear model is found suitable for producing PBLH estimates in marine settings (improving mean bias by 71 m), while an ensemble tree method proves more suitable for PBLH types over land, as indicated by improved biases (13 m mean bias), errors (179 m mean error and 391 m RMSE), and correlations (+0.3) for the models explored. The algorithms are additionally tested on “unseen” data to gauge differences between MLH and PBLH estimates produced from each of the models. The PBLH estimates, composed of information from lidar and thermodynamic profiles, further support the use of ML for an automated method of PBLH prediction. Overall, these improved predictions will help evaluate models and deepen our understanding of PBL-aerosol interactions.},

note = {e2024JD042538 2024JD042538},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2024JD042285,

title = {Impact of Smoke Aerosol Loading on Lightning Characteristics of Pyrocumulonimbus Compared With Other High-Based Thunderstorms},

author = {Elena Dworak and David A. Peterson and Pablo E. Saide and Laura Thapa and Jacob Bortnik},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024JD042285},

doi = {https://doi.org/10.1029/2024JD042285},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {130},

number = {12},

pages = {e2024JD042285},

abstract = {Abstract Pyrocumulonimbus (pyroCb) is a form of deep convection that is generated by the heating from large wildfires and specific meteorology known for producing lightning. We study the lightning characteristics of five pyroCb events in British Columbia, Canada, from June 29 to July 1 of 2021, and compare them to other clean and smoke-filled high-based thunderstorms in the same region and season using ground-based lightning detection data, satellite retrievals, meteorological and atmospheric composition reanalysis, and observed thermodynamic profiles. One large pyroCb event over the Sparks Lake fire that generated persistent overshooting tops had a remarkable amount of lightning activity, with 5,600 total lightning strikes, while the rest of the pyroCb events corresponded with lower injection altitudes and minimal to no observed lightning activity. The cloud-to-cloud (CC) to cloud-to-ground (CG) lightning ratio (CC:CG) in this Sparks Lake pyroCb was significantly higher than in other high-based storms but displayed similar lightning density and slightly lower peak current distributions. All clean and smoke-filled thunderstorms produced significant levels of lightning activity, regardless of their cloud-top altitudes. However, ingestion of smoke significantly reduced the percentage of positive polarity CG strikes when compared to clean cases. These results set a reference for identifying the characteristics of pyrogenic lightning and improved predictions of lightning-caused fire ignitions, which will aid in understanding pyroCb activity and related impacts.},

note = {e2024JD042285 2024JD042285},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-25-7879-2025,

title = {Atmospheric processing and aerosol aging responsible for observed increase in absorptivity of long-range-transported smoke over the southeast Atlantic},

author = {A. A. Fakoya and J. Redemann and P. E. Saide and L. Gao and L. T. Mitchell and C. Howes and A. Dobracki and I. Chang and G. A. Ferrada and K. Pistone and S. E. Leblanc and M. Segal-Rozenhaimer and A. J. Sedlacek III and T. Eck and B. Holben and P. Gupta and E. Lind and P. Zuidema and G. Carmichael and C. J. Flynn},

url = {https://acp.copernicus.org/articles/25/7879/2025/},

doi = {10.5194/acp-25-7879-2025},

year  = {2025},

date = {2025-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {25},

number = {14},

pages = {7879–7902},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-25-6663-2025,

title = {Evaluating spatiotemporal variations and exposure risk of ground-level ozone concentrations across China from 2000 to 2020 using high-resolution satellite-derived data},

author = {Q. He and J. Cao and P. E. Saide and T. Ye and W. Wang and M. Zhang and J. Huang},

url = {https://acp.copernicus.org/articles/25/6663/2025/},

doi = {10.5194/acp-25-6663-2025},

year  = {2025},

date = {2025-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {25},

number = {13},

pages = {6663–6677},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rs17111854,

title = {An Assessment of TROPESS CrIS and TROPOMI CO Retrievals and Their Synergies for the 2020 Western U.S. Wildfires},

author = {Oscar A. Neyra-Nazarrett and Kazuyuki Miyazaki and Kevin W. Bowman and Pablo E. Saide},

url = {https://www.mdpi.com/2072-4292/17/11/1854},

doi = {10.3390/rs17111854},

issn = {2072-4292},

year  = {2025},

date = {2025-01-01},

journal = {Remote Sensing},

volume = {17},

number = {11},

abstract = {The 2020 wildfire season in the Western U.S. was historic in its intensity and impact on the land and atmosphere. This study aims to characterize satellite retrievals of carbon monoxide (CO), a tracer of combustion and signature of those fires, from two key satellite instruments: the Cross-track Infrared Sounder (CrIS) and the Tropospheric Monitoring Instrument (TROPOMI). We evaluate them during this event and assess their synergies. These two retrievals are matched temporally, as the host satellites are in tandem orbit and spatially by aggregating TROPOMI to the CrIS resolution. Both instruments show that the Western U.S. displayed significantly higher daily average CO columns compared to the Central and Eastern U.S. during the wildfires. TROPOMI showed up to a factor of two larger daily averages than CrIS during the most intense fire period, likely due to differences in the vertical sensitivity of the two instruments and representative of near-surface CO abundance near the fires. On the other hand, there was excellent agreement between the instruments in downwind free tropospheric plumes (scatter plot slopes of 0.96–0.99), consistent with their vertical sensitivities and indicative of mostly lofted smoke. Temporally, TROPOMI CO column peaks were delayed relative to the Fire Radiative Power (FRP), and CrIS peaks were delayed with respect to TROPOMI, particularly during the intense initial weeks of September, suggesting boundary layer buildup and ventilation. Satellite retrievals were evaluated using ground-based CO column estimates from the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON), showing Normalized Mean Errors (NMEs) for CrIS and TROPOMI below 32% and 24%, respectively, when compared to all stations studied. While Normalized Mean Bias (NMB) was typically low (absolute value below 15%), there were larger negative biases at Pasadena, likely associated with sharp spatial gradients due to topography and proximity to a large city, which is consistent with previous research. In situ CO profiles from AirCore showed an elevated smoke plume for 15 September 2020, highlighted consistency between TROPOMI and CrIS CO columns for lofted plumes. This study demonstrates that both CrIS and TROPOMI provide complementary information on CO distribution. CrIS’s sensitivity in the middle and lower free troposphere, coupled with TROPOMI’s effectiveness at capturing total columns, offers a more comprehensive view of CO distribution during the wildfires than either retrieval alone. By combining data from both satellites as a ratio, more detailed information about the vertical location of the plumes can potentially be extracted. This approach can enhance air quality models, improve vertical estimation accuracy, and establish a new method for assessing lower tropospheric CO concentrations during significant wildfire events.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1021/acs.est.4c02926,

title = {Unraveling the Influence of Satellite-Observed Land Surface Temperature on High-Resolution Mapping of Ground-Level Ozone Using Interpretable Machine Learning},

author = {Qingqing He and Jingru Cao and Pablo E. Saide and Tong Ye and Weihang Wang},

url = {https://doi.org/10.1021/acs.est.4c02926},

doi = {10.1021/acs.est.4c02926},

year  = {2024},

date = {2024-01-01},

journal = {Environmental Science & Technology},

volume = {58},

number = {36},

pages = {15938-15948},

note = {PMID: 39192575},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2023JD039926,

title = {Evaluation of Wildfire Plume Injection Heights Estimated from Operational Weather Radar Observations Using Airborne Lidar Retrievals},

author = {M. Krishna and P. E. Saide and X. Ye and F. A. Turney and J. W. Hair and M. Fenn and T. Shingler},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2023JD039926},

doi = {https://doi.org/10.1029/2023JD039926},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {129},

number = {9},

pages = {e2023JD039926},

abstract = {Abstract The vertical distribution of wildfire smoke aerosols is important in determining its environmental impacts but existing observations of smoke heights generally do not possess the temporal resolution required to fully resolve the diurnal behavior of wildfire smoke injection. We use Weather Surveillance Radar-1988 Doppler (WSR-88D) dual polarization data to estimate injection heights of Biomass Burning Debris (BBD) generated by fires. We detect BBD as a surrogate for smoke aerosols, which are often collocated with BBD near the fire but are not within the size range detectable by these radars. Injection heights of BBD are derived for 2–10 August 2019, using WSR-88D reflectivity (Z ≥ 10 dBZ) and dual polarization correlation coefficients (0.2 < C.C < 0.9) to study the Williams Flats fire. Results show the expected diurnal cycles with maximum injection heights present during the late afternoon period when the fire's intensity and convective mixing are maximized. WSR-88D and airborne lidar injection height comparisons reveal that this method is sensitive to outliers and generally overpredicts maximum heights by 40%, though mean and median heights are better captured (<20% mean error). WSR-88D heights between the 75th and 90th percentile seem to accurately represent the maximum heights, with the exception of heights estimated during the occurrence of a pyro-cumulonimbus. Location specific mapping of WSR-88D and lidar injection heights reveal that they diverge further away from the fire as expected due to BBD settling. Most importantly, WSR-88D-derived injection height estimates provide near continuous smoke height information, allowing for the study of diurnal variability of smoke injections.},

note = {e2023JD039926 2023JD039926},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2023JD040514,

title = {Forecasting Daily Fire Radiative Energy Using Data Driven Methods and Machine Learning Techniques},

author = {Laura H. Thapa and Pablo E. Saide and Jacob Bortnik and Melinda T. Berman and Arlindo Silva and David A. Peterson and Fangjun Li and Shobha Kondragunta and Ravan Ahmadov and Eric James and Johana Romero-Alvarez and Xinxin Ye and Amber Soja and Elizabeth Wiggins and Emily Gargulinski},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2023JD040514},

doi = {https://doi.org/10.1029/2023JD040514},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {129},

number = {16},

pages = {e2023JD040514},

abstract = {Abstract Increasing impacts of wildfires on Western US air quality highlights the need for forecasts of smoke emissions based on dynamic modeled wildfires. This work utilizes knowledge of weather, fuels, topography, and firefighting, combined with machine learning and other statistical methods, to generate 1- and 2-day forecasts of fire radiative energy (FRE). The models are trained on data covering 2019 and 2021 and evaluated on data for 2020. For the 1-day (2-day) forecasts, the random forest model shows the most skill, explaining 48% (25%) of the variance in observed daily FRE when trained on all available predictors compared to the 2% (<0%) of variance explained by persistence for the extreme fire year of 2020. The random forest model also shows improved skill in forecasting day-to-day increases and decreases in FRE, with 28% (39%) of observed increase (decrease) days predicted, and increase (decrease) days are identified with 62% (60%) accuracy. Error in the random forest increases with FRE, and the random forest tends toward persistence under severe fire weather. Sensitivity analysis shows that near-surface weather and the latest observed FRE contribute the most to the skill of the model. When the random forest model was trained on subsets of the training data produced by agencies (e.g., the Canadian or US Forest Services), comparable if not better performance was achieved (1-day R2 = 0.39–0.48, 2-day R2 = 0.13–0.34). FRE is used to compute emissions, so these results demonstrate potential for improved fire emissions forecasts for air quality models.},

note = {e2023JD040514 2023JD040514},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-23-4283-2023,

title = {On the differences in the vertical distribution of modeled aerosol optical 

depth over the southeastern Atlantic},

author = {I. Chang and L. Gao and C. J. Flynn and Y. Shinozuka and S. J. Doherty and M. S. Diamond and K. M. Longo and G. A. Ferrada and G. R. Carmichael and P. Castellanos and A. M. Silva and P. E. Saide and C. Howes and Z. Xue and M. Mallet and R. Govindaraju and Q. Wang and Y. Cheng and Y. Feng and S. P. Burton and R. A. Ferrare and S. E. LeBlanc and M. S. Kacenelenbogen and K. Pistone and M. Segal-Rozenhaimer and K. G. Meyer and J. -M. Ryoo and L. Pfister and A. A. Adebiyi and R. Wood and P. Zuidema and S. A. Christopher and J. Redemann},

url = {https://acp.copernicus.org/articles/23/4283/2023/},

doi = {10.5194/acp-23-4283-2023},

year  = {2023},

date = {2023-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {23},

number = {7},

pages = {4283–4309},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-23-4775-2023,

title = {An attribution of the low single-scattering albedo of biomass burning aerosol over the southeastern Atlantic},

author = {A. Dobracki and P. Zuidema and S. G. Howell and P. Saide and S. Freitag and A. C. Aiken and S. P. Burton and A. J. Sedlacek III and J. Redemann and R. Wood},

url = {https://acp.copernicus.org/articles/23/4775/2023/},

doi = {10.5194/acp-23-4775-2023},

year  = {2023},

date = {2023-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {23},

number = {8},

pages = {4775–4799},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-23-13911-2023,

title = {Biomass-burning smoke's properties and its interactions with marine 

stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns},

author = {C. Howes and P. E. Saide and H. Coe and A. Dobracki and S. Freitag and J. M. Haywood and S. G. Howell and S. Gupta and J. Uin and M. Kacarab and C. Kuang and L. R. Leung and A. Nenes and G. M. McFarquhar and J. Podolske and J. Redemann and A. J. Sedlacek and K. L. Thornhill and J. P. S. Wong and R. Wood and H. Wu and Y. Zhang and J. Zhang and P. Zuidema},

url = {https://acp.copernicus.org/articles/23/13911/2023/},

doi = {10.5194/acp-23-13911-2023},

year  = {2023},

date = {2023-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {23},

number = {21},

pages = {13911–13940},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{amt-16-2037-2023,

title = {Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic},

author = {E. D. Lenhardt and L. Gao and J. Redemann and F. Xu and S. P. Burton and B. Cairns and I. Chang and R. A. Ferrare and C. A. Hostetler and P. E. Saide and C. Howes and Y. Shinozuka and S. Stamnes and M. Kacarab and A. Dobracki and J. Wong and S. Freitag and A. Nenes},

url = {https://amt.copernicus.org/articles/16/2037/2023/},

doi = {10.5194/amt-16-2037-2023},

year  = {2023},

date = {2023-01-01},

journal = {Atmospheric Measurement Techniques},

volume = {16},

number = {7},

pages = {2037–2054},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pagonis2023impact,

title = {Impact of Biomass Burning Organic Aerosol Volatility on Smoke Concentrations Downwind of Fires},

author = {Demetrios Pagonis and Vanessa Selimovic and Pedro Campuzano-Jost and Hongyu Guo and Douglas A Day and Melinda K Schueneman and Benjamin A Nault and Matthew M Coggon and Joshua P DiGangi and Glenn S Diskin and others},

year  = {2023},

date = {2023-01-01},

journal = {Environmental Science & Technology},

publisher = {ACS Publications},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2023GL104824,

title = {Estimating Fire Radiative Power Using Weather Radar Products for Wildfires},

author = {P. E. Saide and M. Krishna and X. Ye and L. H. Thapa and F. Turney and C. Howes and C. C. Schmidt},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2023GL104824},

doi = {https://doi.org/10.1029/2023GL104824},

year  = {2023},

date = {2023-01-01},

journal = {Geophysical Research Letters},

volume = {50},

number = {21},

pages = {e2023GL104824},

abstract = {Abstract Satellite-based Fire radiative power (FRP) retrievals are used to track wildfire activity but are sometimes not possible or have large uncertainties. Here, we show that weather radar products including composite and base reflectivity and equivalent rainfall integrated in the vicinity of the fires show strong correlation with hourly FRP for multiple fires during 2019–2020. Correlation decreases when radar beams are blocked by topography and when there is significant ground clutter (GC) and anomalous propagation (AP). GC/AP can be effectively removed using a machine learning classifier trained with radar retrieved correlation coefficient, velocity, and spectrum width. We find a power-law best describes the relationship between radar products and FRP for multiple fires combined (0.67–0.76 R2). Radar-based FRP estimates can be used to fill gaps in satellite FRP created by cloud cover and show great potential to overcome satellite FRP biases occurring during extreme fire events.},

note = {e2023GL104824 2023GL104824},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1525/elementa.2022.00096,

title = {WRF-Chem quantification of transport events and emissions sensitivity in Korea during KORUS-AQ},

author = {Beiming Tang and Pablo E. Saide and Meng Gao and Gregory R. Carmichael and Charles O. Stanier},

url = {https://doi.org/10.1525/elementa.2022.00096},

doi = {10.1525/elementa.2022.00096},

issn = {2325-1026},

year  = {2023},

date = {2023-01-01},

journal = {Elementa: Science of the Anthropocene},

volume = {11},

number = {1},

abstract = {To quantify the relative roles of long-range transport (LRT) versus locally emitted aerosol and ozone precursors during polluted periods in Korea, high-resolution (4 km) Weather Research and Forecasting with Chemistry model simulations were performed. The model was evaluated using surface and airborne observations collected during the KORea and United States Air Quality campaign. Ozone above 40 ppb had mean bias of −5.9 ppb. PM2.5 was biased high (8.2 µg/m3), with a relative bias of 30% given the mean observed value of 26.8 µg/m3. The absolute amounts and shifts between phases for all PM2.5 species except nitrate reasonably match observations across all 4 phases. Notable limitations include an underestimation of nighttime planetary boundary layer height. Transport versus domestic emissions influence was studied by model runs with perturbed emissions and by comparing east-west fluxes over the Yellow Sea to Korean emissions and other normalization metrics. Domestic anthropogenic emission contributions to surface air quality were quantified by location across Korea, segregated by synoptic meteorological phase. The largest contributions from Korean emissions were found under high-pressure stagnant conditions and the smallest for conditions with strong westerly winds. For example, at Seoul, domestic contributions of PM2.5 averaged 49% and 29% in the aforementioned meteorological phases, respectively. Surface concentrations of NOx and toluene in Seoul were over 85% due to domestic emissions. CO and black carbon had both local and remote contributions. Nitrate and ammonium contributions varied greatly by phases in Seoul, with 7%–51% nitrate and 42%–70% of ammonium from remote sources. Variation in direction (west-to-east vs. east-to-west) and magnitude of fluxes support the model sensitivity results. Analysis using fluxes facilitates the quantification of source contributions for secondary species and, in many cases, can be done using a single model run or reanalysis result. The analysis presented shows the importance of using models with high spatial resolution to capture pollutant transport and mixing around Korea. However, there remain uncertainties in secondary aerosol production mechanisms and indications that local production at times could be higher than those modeled in this analysis. Therefore, the results presented here should be viewed as an upper limit on the importance of LRT.},

note = {00096},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2023JD038873,

title = {Sensitivity of Burned Area and Fire Radiative Power Predictions to Containment Efforts, Fuel Density, and Fuel Moisture Using WRF-Fire},

author = {Francis A. Turney and Pablo E. Saide and Pedro A. Jimenez Munoz and Domingo Muñoz-Esparza and Edward J. Hyer and David A. Peterson and Maria E. Frediani and Timothy W. Juliano and Amy L. DeCastro and Branko Kosović and Xinxin Ye and Laura H. Thapa},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2023JD038873},

doi = {https://doi.org/10.1029/2023JD038873},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {128},

number = {18},

pages = {e2023JD038873},

abstract = {Abstract Predicting the evolution of burned area, smoke emissions, and energy release from wildfires is crucial to air quality forecasting and emergency response planning yet has long posed a significant scientific challenge. Here we compare predictions of burned area and fire radiative power from the coupled weather/fire-spread model WRF-Fire (Weather and Research Forecasting Tool with fire code), against simpler methods typically used in air quality forecasts. We choose the 2019 Williams Flats Fire as our test case due to a wealth of observations and ignite the fire on different days and under different configurations. Using a novel re-gridding scheme, we compare WRF-Fire's heat output to geostationary satellite data at 1-hr temporal resolution. We also evaluate WRF-Fire's time-resolved burned area against high-resolution imaging from the National Infrared Operations aircraft data. Results indicate that for this study, accounting for containment efforts in WRF-Fire simulations makes the biggest difference in achieving accurate results for daily burned area predictions. When incorporating novel containment line inputs, fuel density increases, and fuel moisture observations into the model, the error in average daily burned area is 30% lower than persistence forecasting over a 5-day forecast. Prescribed diurnal cycles and those resolved by WRF-Fire simulations show a phase offset of at least an hour ahead of observations, likely indicating the need for dynamic fuel moisture schemes. This work shows that with proper configuration and input data, coupled weather/fire-spread modeling has the potential to improve smoke emission forecasts.},

note = {e2023JD038873 2023JD038873},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2022JD037758,

title = {Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ)},

author = {Carsten Warneke and Joshua P. Schwarz and Jack Dibb and Olga Kalashnikova and Gregory Frost and Jassim Al-Saad and Steven S. Brown and Wm. Alan Brewer and Amber Soja and Felix C. Seidel and Rebecca A. Washenfelder and Elizabeth B. Wiggins and Richard H. Moore and Bruce E. Anderson and Carolyn Jordan and Tara I. Yacovitch and Scott C. Herndon and Shang Liu and Toshihiro Kuwayama and Daniel Jaffe and Nancy Johnston and Vanessa Selimovic and Robert Yokelson and David M. Giles and Brent N. Holben and Philippe Goloub and Ioana Popovici and Michael Trainer and Aditya Kumar and R. Bradley Pierce and David Fahey and James Roberts and Emily M. Gargulinski and David A. Peterson and Xinxin Ye and Laura H. Thapa and Pablo E. Saide and Charles H. Fite and Christopher D. Holmes and Siyuan Wang and Matthew M. Coggon and Zachary C. J. Decker and Chelsea E. Stockwell and Lu Xu and Georgios Gkatzelis and Kenneth Aikin and Barry Lefer and Jackson Kaspari and Debora Griffin and Linghan Zeng and Rodney Weber and Meredith Hastings and Jiajue Chai and Glenn M. Wolfe and Thomas F. Hanisco and Jin Liao and Pedro Campuzano Jost and Hongyu Guo and Jose L. Jimenez and James Crawford and The FIREX-AQ Science Team},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022JD037758},

doi = {https://doi.org/10.1029/2022JD037758},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {128},

number = {2},

pages = {e2022JD037758},

abstract = {Abstract The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was a multi-agency, inter-disciplinary research effort to: (a) obtain detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires using aircraft, satellites and ground-based instruments, (b) make extensive suborbital remote sensing measurements of fire dynamics, (c) assess local, regional, and global modeling of fires, and (d) strengthen connections to observables on the ground such as fuels and fuel consumption and satellite products such as burned area and fire radiative power. From Boise, ID western wildfires were studied with the NASA DC-8 and two NOAA Twin Otter aircraft. The high-altitude NASA ER-2 was deployed from Palmdale, CA to observe some of these fires in conjunction with satellite overpasses and the other aircraft. Further research was conducted on three mobile laboratories and ground sites, and 17 different modeling forecast and analyses products for fire, fuels and air quality and climate implications. From Salina, KS the DC-8 investigated 87 smaller fires in the Southeast with remote and in-situ data collection. Sampling by all platforms was designed to measure emissions of trace gases and aerosols with multiple transects to capture the chemical transformation of these emissions and perform remote sensing observations of fire and smoke plumes under day and night conditions. The emissions were linked to fuels consumed and fire radiative power using orbital and suborbital remote sensing observations collected during overflights of the fires and smoke plumes and ground sampling of fuels.},

note = {e2022JD037758 2022JD037758},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{yu2023synergistic,

title = {Synergistic combination of information from ground observations, geostationary satellite, and air quality modeling towards improved PM2. 5 predictability},

author = {Jinhyeok Yu and Chul H Song and Dogyeong Lee and Sojin Lee and Hyun S Kim and Kyung M Han and Seohui Park and Jungho Im and Soon-Young Park and Moongu Jeon and others},

year  = {2023},

date = {2023-01-01},

journal = {npj Climate and Atmospheric Science},

volume = {6},

number = {1},

pages = {41},

publisher = {Nature Publishing Group UK London},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-22-12113-2022,

title = {Cloud adjustments from large-scale smoke–circulation interactions strongly modulate the southeastern Atlantic stratocumulus-to-cumulus transition},

author = {M. S. Diamond and P. E. Saide and P. Zuidema and A. S. Ackerman and S. J. Doherty and A. M. Fridlind and H. Gordon and C. Howes and J. Kazil and T. Yamaguchi and J. Zhang and G. Feingold and R. Wood},

url = {https://acp.copernicus.org/articles/22/12113/2022/},

doi = {10.5194/acp-22-12113-2022},

year  = {2022},

date = {2022-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {22},

number = {18},

pages = {12113–12151},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-22-1-2022,

title = {Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic},

author = {S. J. Doherty and P. E. Saide and P. Zuidema and Y. Shinozuka and G. A. Ferrada and H. Gordon and M. Mallet and K. Meyer and D. Painemal and S. G. Howell and S. Freitag and A. Dobracki and J. R. Podolske and S. P. Burton and R. A. Ferrare and C. Howes and P. Nabat and G. R. Carmichael and A. Silva and K. Pistone and I. Chang and L. Gao and R. Wood and J. Redemann},

url = {https://acp.copernicus.org/articles/22/1/2022/},

doi = {10.5194/acp-22-1-2022},

year  = {2022},

date = {2022-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {22},

number = {1},

pages = {1–46},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LEE2022118921,

title = {Impacts of uncertainties in emissions on aerosol data assimilation and short-term PM2.5 predictions over Northeast Asia},

author = {Sojin Lee and Chul Han Song and Kyung Man Han and Daven K. Henze and Kyunghwa Lee and Jinhyeok Yu and Jung-Hun Woo and Jia Jung and Yunsoo Choi and Pablo E. Saide and Gregory R. Carmichael},

url = {https://www.sciencedirect.com/science/article/pii/S1352231021007433},

doi = {https://doi.org/10.1016/j.atmosenv.2021.118921},

issn = {1352-2310},

year  = {2022},

date = {2022-01-01},

journal = {Atmospheric Environment},

volume = {271},

pages = {118921},

abstract = {To improve PM2.5 predictions in Northeast Asia, we estimated a new background error covariance matrix (BEC) for aerosol data assimilation using surface PM2.5 observations. In contrast to the conventional method of BEC estimation that uses perturbations in meteorological data, this method additionally considered the perturbations using two different emission inventories. By taking the emission uncertainty into account, we found that the standard deviations in the BEC were significantly increased. The standard deviations became around three times larger than those in the conventional method at the surface. The impacts of the new BEC were then tested for the prediction of surface PM2.5 over Northeast Asia using the Community Multiscale Air Quality (CMAQ) model initialized by three-dimensional variational method (3D-VAR). The surface PM2.5 data measured at 154 sites in South Korea and 1535 sites in China were assimilated every 6 h during the campaign period of the Korea-United States Air Quality Study (KORUS-AQ) (1 May–14 June 2016). The data assimilation with the new BEC showed better agreement with the surface PM2.5 observations than with the BEC from the conventional method. Our method was also more consistent with the observations in 24-h PM2.5 predictions than the conventional method (specifically, with a ∼44% reduction of negative biases). We concluded that increased standard deviations, together with updated horizontal and vertical length scales in the new BEC, improved the data assimilation and short-term predictions of the surface PM2.5. This paper also suggests several research efforts to further improve the BEC for better short-term PM2.5 predictions in Northeast Asia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{MeasurementsfrominsideaThunderstormDrivenbyWildfireThe2019FIREXAQFieldExperiment,

title = {Measurements from inside a Thunderstorm Driven by Wildfire: The 2019 FIREX-AQ Field Experiment},

author = {David A. Peterson and Laura H. Thapa and Pablo E. Saide and Amber J. Soja and Emily M. Gargulinski and Edward J. Hyer and Bernadett Weinzierl and Maximilian Dollner and Manuel Schöberl and Philippe P. Papin and Shobha Kondragunta and Christopher P. Camacho and Charles Ichoku and Richard H. Moore and Johnathan W. Hair and James H. Crawford and Philip E. Dennison and Olga V. Kalashnikova and Christel E. Bennese and Thaopaul P. Bui and Joshua P. DiGangi and Glenn S. Diskin and Marta A. Fenn and Hannah S. Halliday and Jose Jimenez and John B. Nowak and Claire Robinson and Kevin Sanchez and Taylor J. Shingler and Lee Thornhill and Elizabeth B. Wiggins and Edward Winstead and Chuanyu Xu},

url = {https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-21-0049.1/BAMS-D-21-0049.1.xml},

doi = {10.1175/BAMS-D-21-0049.1},

year  = {2022},

date = {2022-01-01},

journal = {Bulletin of the American Meteorological Society},

publisher = {American Meteorological Society},

address = {Boston MA, USA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2022GL099175,

title = {Understanding the Evolution of Smoke Mass Extinction Efficiency Using Field Campaign Measurements},

author = {Pablo E. Saide and Laura H. Thapa and Xinxin Ye and Demetrios Pagonis and Pedro Campuzano-Jost and Hongyu Guo and Melinda L. Schuneman and Jose-Luis Jimenez and Richard Moore and Elizabeth Wiggins and Edward Winstead and Claire Robinson and Lee Thornhill and Kevin Sanchez and Nicholas L. Wagner and Adam Ahern and Joseph M. Katich and Anne E. Perring and Joshua P. Schwarz and Ming Lyu and Christopher D. Holmes and Johnathan W. Hair and Marta A. Fenn and Taylor J. Shingler},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022GL099175},

doi = {https://doi.org/10.1029/2022GL099175},

year  = {2022},

date = {2022-01-01},

journal = {Geophysical Research Letters},

volume = {49},

number = {18},

pages = {e2022GL099175},

abstract = {Abstract Aerosol mass extinction efficiency (MEE) is a key aerosol property used to connect aerosol optical properties with aerosol mass concentrations. Using measurements of smoke obtained during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign we find that mid-visible smoke MEE can change by a factor of 2–3 between fresh smoke (<2 hr old) and one-day-old smoke. While increases in aerosol size partially explain this trend, changes in the real part of the aerosol refractive index (real(n)) are necessary to provide closure assuming Mie theory. Real(n) estimates derived from multiple days of FIREX-AQ measurements increase with age (from 1.40 – 1.45 to 1.5–1.54 from fresh to one-day-old) and are found to be positively correlated with organic aerosol oxidation state and aerosol size, and negatively correlated with smoke volatility. Future laboratory, field, and modeling studies should focus on better understanding and parameterizing these relationships to fully represent smoke aging.},

note = {e2022GL099175 2022GL099175},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{thapa2022heat,

title = {Heat flux assumptions contribute to overestimation of wildfire smoke injection into the free troposphere},

author = {Laura H Thapa and Xinxin Ye and Johnathan W Hair and Marta A Fenn and Taylor Shingler and Shobha Kondragunta and Charles Ichoku and RoseAnne Dominguez and Luke Ellison and Amber J Soja and others},

year  = {2022},

date = {2022-01-01},

journal = {Communications Earth & Environment},

volume = {3},

number = {1},

pages = {236},

publisher = {Nature Publishing Group UK London},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2022JD036808,

title = {Assessing Vertical Allocation of Wildfire Smoke Emissions Using Observational Constraints From Airborne Lidar in the Western U.S.},

author = {Xinxin Ye and Pablo E. Saide and Johnathan Hair and Marta Fenn and Taylor Shingler and Amber Soja and Emily Gargulinski and Elizabeth Wiggins},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022JD036808},

doi = {https://doi.org/10.1029/2022JD036808},

year  = {2022},

date = {2022-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {127},

number = {21},

pages = {e2022JD036808},

abstract = {Abstract Wildfire emissions are a key contributor of carbonaceous aerosols and trace gases to the atmosphere. Induced by buoyant lifting, smoke plumes can be injected into the free troposphere and lower stratosphere, which by consequence significantly affects the magnitude and distance of their influences on air quality and radiation budget. However, the vertical allocation of emissions when smoke escapes the planetary boundary layer (PBL) and the mechanism modulating it remain unclear. We present an inverse modeling framework to estimate the wildfire emissions, with their temporal and vertical evolution being constrained by assimilating aerosol extinction profiles observed from the airborne Differential Absorption Lidar-High Spectral Resolution Lidar during the Fire Influence on Regional to Global Environments and Air Quality field campaign. Three fire events in the western U.S., which exhibit free-tropospheric injections are examined. The constrained smoke emissions indicate considerably larger fractions of smoke injected above the PBL (f>PBL, 80%–94%) versus the column total, compared to those estimated by the WRF-Chem model using the default plume rise option (12%–52%). The updated emission profiles yield improvements for the simulated vertical structures of the downwind transported smoke, but limited refinement of regional smoke aerosol optical depth distributions due to the spatiotemporal coverage of flight observations. These results highlight the significance of improving vertical allocation of fire emissions on advancing the modeling and forecasting of the environmental impacts of smoke.},

note = {e2022JD036808 2022JD036808},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rs14236113,

title = {Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S.},

author = {Xinxin Ye and Mina Deshler and Alexi Lyapustin and Yujie Wang and Shobha Kondragunta and Pablo Saide},

url = {https://www.mdpi.com/2072-4292/14/23/6113},

doi = {10.3390/rs14236113},

issn = {2072-4292},

year  = {2022},

date = {2022-01-01},

journal = {Remote Sensing},

volume = {14},

number = {23},

abstract = {Satellite remote sensing of aerosol optical depth (AOD) is essential for detection, characterization, and forecasting of wildfire smoke. In this work, we evaluate the AOD (550 nm) retrievals during the extreme wildfire events over the western U.S. in September 2020. Three products are analyzed, including the Moderate-resolution Imaging Spectroradiometers (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) product collections C6.0 and C6.1, and the NOAA-20 Visible Infrared Imaging Radiometer (VIIRS) AOD from the NOAA Enterprise Processing System (EPS) algorithm. Compared with the Aerosol Robotic Network (AERONET) data, all three products show strong linear correlations with MAIAC C6.1 and VIIRS presenting overall low bias (<0.06). The accuracy of MAIAC C6.1 is found to be substantially improved with respect to MAIAC C6.0 that drastically underestimated AOD over thick smoke, which validates the effectiveness of updates made in MAIAC C6.1 in terms of an improved representation of smoke aerosol optical properties. VIIRS AOD exhibits comparable uncertainty with MAIAC C6.1 with a slight tendency of increased positive bias over the AERONET AOD range of 0.5-3.0. Averaging coincident retrievals from MAIAC C6.1 and VIIRS provides a lower root mean square error and higher correlation than for the individual products, motivating the benefit of blending these datasets. MAIAC C6.1 and VIIRS are further compared to provide insights on their retrieval strategy. When gridded at 0.1° resolution, MAIAC C6.1 and VIIRS provide similar monthly AOD distribution patterns and the latter exhibits a slightly higher domain average. On daily scale, over thick plumes near fire sources, MAIAC C6.1 reports more valid retrievals where VIIRS tends to have retrievals designated as low or medium quality, which tends to be due to internal quality checks. Over transported smoke near scattered clouds, VIIRS provides better retrieval coverage than MAIAC C6.1 owing to its higher spatial resolution, pixel-level processing, and less strict cloud masking. These results can be used as a guide for applications of satellite AOD retrievals during wildfire events and provide insights on future improvement of retrieval algorithms under heavy smoke conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2020JD032663,

title = {Evaluating the Mobile Flux Plane (MFP) Method to Estimate Methane Emissions Using Large Eddy Simulations (LES)},

author = {Rajesh Kumar and Douglas A. Mitchell and Daniel F. Steinhoff and Pablo Saide and Branko Kosovic and Nicole Downey and Doug Blewitt and Luca Delle Monache},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020JD032663},

doi = {https://doi.org/10.1029/2020JD032663},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {126},

number = {5},

pages = {e2020JD032663},

abstract = {Abstract This study evaluates the efficacy of the mobile flux plane (MFP) method to derive methane emissions from oil and gas production fields using a first-of-its-kind high-resolution methane concentration data set. Transport and dispersion of methane emissions from seven hypothetical well pads generated with an oil field emission simulator is simulated every second at 10 m resolution using the Weather Research and Forecasting (WRF) model in large eddy simulation mode. The time varying WRF-generated methane concentration data set is sampled by a simulated MFP system downwind of the seven well pads at five sampling distances of 50, 75, 100, 125, and 150 m. Several key findings highlight the significant variability in MFP emission rate estimates induced by atmospheric turbulence and variable source emission rates. Natural atmospheric turbulence alone was found to generate significant variability (33%–75%) in the MFP emission estimates with constant emission rates at the source location. It was also found that turbulent wind speed fluctuations over the duration of a transect can also affect MFP estimates up to about ±50% through convergence (divergence) that increases (decreases) methane concentrations, and by its effect on the assumption of steady winds over the duration of the transect. It was further found that the MFP method typically estimated about 19%–33% and 51%–75% of known site emission rates using the trapezoidal and Gaussian fit integration methods, respectively. Thus, methane concentrations would need to be measured to a much higher elevation to generate robust and accurate methane emission rate estimates.},

note = {e2020JD032663 2020JD032663},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-21-9643-2021,

title = {Exploring the elevated water vapor signal associated with the free tropospheric biomass burning plume over the southeast Atlantic Ocean},

author = {K. Pistone and P. Zuidema and R. Wood and M. Diamond and A. M. Silva and G. Ferrada and P. E. Saide and R. Ueyama and J. -M. Ryoo and L. Pfister and J. Podolske and D. Noone and R. Bennett and E. Stith and G. Carmichael and J. Redemann and C. Flynn and S. LeBlanc and M. Segal-Rozenhaimer and Y. Shinozuka},

url = {https://acp.copernicus.org/articles/21/9643/2021/},

doi = {10.5194/acp-21-9643-2021},

year  = {2021},

date = {2021-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {21},

number = {12},

pages = {9643–9668},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-21-1507-2021,

title = {An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their 

intEractionS) project: aerosol–cloud–radiation interactions in the southeast 

Atlantic basin},

author = {J. Redemann and R. Wood and P. Zuidema and S. J. Doherty and B. Luna and S. E. LeBlanc and M. S. Diamond and Y. Shinozuka and I. Y. Chang and R. Ueyama and L. Pfister and J. -M. Ryoo and A. N. Dobracki and A. M. Silva and K. M. Longo and M. S. Kacenelenbogen and C. J. Flynn and K. Pistone and N. M. Knox and S. J. Piketh and J. M. Haywood and P. Formenti and M. Mallet and P. Stier and A. S. Ackerman and S. E. Bauer and A. M. Fridlind and G. R. Carmichael and P. E. Saide and G. A. Ferrada and S. G. Howell and S. Freitag and B. Cairns and B. N. Holben and K. D. Knobelspiesse and S. Tanelli and T. S. L'Ecuyer and A. M. Dzambo and O. O. Sy and G. M. McFarquhar and M. R. Poellot and S. Gupta and J. R. O'Brien and A. Nenes and M. Kacarab and J. P. S. Wong and J. D. Small-Griswold and K. L. Thornhill and D. Noone and J. R. Podolske and K. S. Schmidt and P. Pilewskie and H. Chen and S. P. Cochrane and A. J. Sedlacek and T. J. Lang and E. Stith and M. Segal-Rozenhaimer and R. A. Ferrare and S. P. Burton and C. A. Hostetler and D. J. Diner and F. C. Seidel and S. E. Platnick and J. S. Myers and K. G. Meyer and D. A. Spangenberg and H. Maring and L. Gao},

url = {https://acp.copernicus.org/articles/21/1507/2021/},

doi = {10.5194/acp-21-1507-2021},

year  = {2021},

date = {2021-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {21},

number = {3},

pages = {1507–1563},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-21-14427-2021,

title = {Evaluation and intercomparison of wildfire smoke forecasts from 

multiple modeling systems for the 2019 Williams Flats fire},

author = {X. Ye and P. Arab and R. Ahmadov and E. James and G. A. Grell and B. Pierce and A. Kumar and P. Makar and J. Chen and D. Davignon and G. R. Carmichael and G. Ferrada and J. McQueen and J. Huang and R. Kumar and L. Emmons and F. L. Herron-Thorpe and M. Parrington and R. Engelen and V. -H. Peuch and A. Silva and A. Soja and E. Gargulinski and E. Wiggins and J. W. Hair and M. Fenn and T. Shingler and S. Kondragunta and A. Lyapustin and Y. Wang and B. Holben and D. M. Giles and P. E. Saide},

url = {https://acp.copernicus.org/articles/21/14427/2021/},

doi = {10.5194/acp-21-14427-2021},

year  = {2021},

date = {2021-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {21},

number = {18},

pages = {14427–14469},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{amt-13-2523-2020,

title = {Assessment of chemNO_2 observations during DISCOVER-AQ and KORUS-AQ field campaigns},

author = {S. Choi and L. N. Lamsal and M. Follette-Cook and J. Joiner and N. A. Krotkov and W. H. Swartz and K. E. Pickering and C. P. Loughner and W. Appel and G. Pfister and P. E. Saide and R. C. Cohen and A. J. Weinheimer and J. R. Herman},

url = {https://www.atmos-meas-tech.net/13/2523/2020/},

doi = {10.5194/amt-13-2523-2020},

year  = {2020},

date = {2020-01-01},

journal = {Atmospheric Measurement Techniques},

volume = {13},

number = {5},

pages = {2523–2546},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-20-11491-2020,

title = {Modeling the smoky troposphere of the southeast Atlantic: a 

comparison to ORACLES airborne observations from September of 2016},

author = {Y. Shinozuka and P. E. Saide and G. A. Ferrada and S. P. Burton and R. Ferrare and S. J. Doherty and H. Gordon and K. Longo and M. Mallet and Y. Feng and Q. Wang and Y. Cheng and A. Dobracki and S. Freitag and S. G. Howell and S. LeBlanc and C. Flynn and M. Segal-Rosenhaimer and K. Pistone and J. R. Podolske and E. J. Stith and J. R. Bennett and G. R. Carmichael and A. Silva and R. Govindaraju and R. Leung and Y. Zhang and L. Pfister and J. -M. Ryoo and J. Redemann and R. Wood and P. Zuidema},

url = {https://acp.copernicus.org/articles/20/11491/2020/},

doi = {10.5194/acp-20-11491-2020},

year  = {2020},

date = {2020-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {20},

number = {19},

pages = {11491–11526},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-19-1801-2019,

title = {A top-down assessment using OMI chemNO_2 suggests an underestimate in the 

chemNO_mathitx emissions inventory in Seoul, South Korea, during 

KORUS-AQ},

author = {D. L. Goldberg and P. E. Saide and L. N. Lamsal and B. Foy and Z. Lu and J. -H. Woo and Y. Kim and J. Kim and M. Gao and G. Carmichael and D. G. Streets},

url = {https://www.atmos-chem-phys.net/19/1801/2019/},

doi = {10.5194/acp-19-1801-2019},

year  = {2019},

date = {2019-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {19},

number = {3},

pages = {1801–1818},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1029/2018JD029009,

title = {Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals},

author = {Rajesh Kumar and Luca Delle Monache and Jamie Bresch and Pablo E. Saide and Youhua Tang and Zhiquan Liu and Arlindo M. Silva and Stefano Alessandrini and Gabriele Pfister and David Edwards and Pius Lee and Irina Djalalova},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018JD029009},

doi = {10.1029/2018JD029009},

year  = {2019},

date = {2019-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {124},

number = {5},

pages = {2753-2773},

abstract = {Abstract This study develops a new approach to improve simulations of the particulate matter of aerodynamic diameter smaller than 2.5 μm (PM2.5) in the Community Multiscale Air Quality (CMAQ) model via assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals using the Gridpoint Statistical Interpolation (GSI) system. In contrast to previous studies that only consider errors due to transport, our computation of the background error covariance matrix incorporates uncertainties in anthropogenic emissions. To understand the impact of this approach, three experiments (one background and two assimilations) are performed over the contiguous United States (CONUS) from 15 July to 14 August 2014. The background CMAQ experiment significantly underestimates both the MODIS AOD and surface PM2.5 levels. MODIS AOD assimilation pushes both the CMAQ AOD and surface PM2.5 distributions toward the observed distributions, but CMAQ still underestimates the observations. Averaged over CONUS, the two assimilation experiments with and without including the anthropogenic emission uncertainties improve the correlation coefficient between the model and independent observations of PM2.5 by ~67% and ~48%, respectively, and reduces the mean bias by ~38% and ~10%, respectively. The assimilation improves the model performance everywhere over CONUS, except the New York and Wisconsin, where CMAQ overestimates the observed PM2.5 during nighttime after assimilation likely because of overcorrection of aerosol mass concentrations by the AOD assimilation. Future work should incorporate uncertainties in other processes (biomass burning and biogenic emissions, deposition, chemistry, transport, and boundary conditions) to further enhance the value of assimilating spaceborne AOD retrievals.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-19-4963-2019,

title = {Simulation of the transport, vertical distribution, optical 

properties and radiative impact of smoke aerosols with the ALADIN regional 

climate model during the ORACLES-2016 and LASIC experiments},

author = {M. Mallet and P. Nabat and P. Zuidema and J. Redemann and A. M. Sayer and M. Stengel and S. Schmidt and S. Cochrane and S. Burton and R. Ferrare and K. Meyer and P. Saide and H. Jethva and O. Torres and R. Wood and D. Saint Martin and R. Roehrig and C. Hsu and P. Formenti},

url = {https://www.atmos-chem-phys.net/19/4963/2019/},

doi = {10.5194/acp-19-4963-2019},

year  = {2019},

date = {2019-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {19},

number = {7},

pages = {4963–4990},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Burton:18,

title = {Calibration of a high spectral resolution lidar using a Michelson interferometer, with data examples from ORACLES},

author = {S. P. Burton and C. A. Hostetler and A. L. Cook and J. W. Hair and S. T. Seaman and S. Scola and D. B. Harper and J. A. Smith and M. A. Fenn and R. A. Ferrare and P. E. Saide and E. V. Chemyakin and D. Müller},

url = {http://ao.osa.org/abstract.cfm?URI=ao-57-21-6061},

doi = {10.1364/AO.57.006061},

year  = {2018},

date = {2018-07-01},

journal = {Appl. Opt.},

volume = {57},

number = {21},

pages = {6061–6075},

publisher = {OSA},

abstract = {The NASA Langley airborne second-generation High Spectral Resolution Lidar (HSRL-2) uses a density-tuned field-widened Michelson interferometer to implement the HSRL technique at 355 nm. The Michelson interferometer optically separates the received backscattered light between two channels, one of which is dominated by molecular backscattering, while the other contains most of the light backscattered by particles. This interferometer achieves high and stable contrast ratio, defined as the ratio of particulate backscatter signal received by the two channels. We show that a high and stable contrast ratio is critical for precise and accurate backscatter and extinction retrievals. Here, we present retrieval equations that take into account the incomplete separation of particulate and molecular backscatter in the measurement channels. We also show how the accuracy of the contrast ratio assessment propagates to error in the optical properties. For both backscattering and extinction, larger errors are produced by underestimates of the contrast ratio (compared to overestimates), more extreme aerosol loading, and—most critically—smaller true contrast ratios. We show example results from HSRL-2 aboard the NASA ER-2 aircraft from the 2016 ORACLES field campaign in the southeast Atlantic, off the coast of Africa, during the biomass burning season. We include a case study where smoke aerosol in two adjacent altitude layers showed opposite differences in extinction- and backscatter-related Ångström exponents and a reversal of the lidar ratio spectral dependence, signatures which are shown to be consistent with a relatively modest difference in smoke particle size.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-18-16863-2018,

title = {Impacts of physical parameterization on prediction of ethane concentrations for oil and gas emissions in WRF-Chem},

author = {M. Abdi-Oskouei and G. Pfister and F. Flocke and N. Sobhani and P. Saide and A. Fried and D. Richter and P. Weibring and J. Walega and G. Carmichael},

url = {https://www.atmos-chem-phys.net/18/16863/2018/},

doi = {10.5194/acp-18-16863-2018},

year  = {2018},

date = {2018-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {18},

number = {23},

pages = {16863–16883},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-18-14623-2018,

title = {Time-dependent entrainment of smoke presents an observational challenge for 

assessing aerosol–cloud interactions over the southeast Atlantic Ocean},

author = {M. S. Diamond and A. Dobracki and S. Freitag and J. D. Small Griswold and A. Heikkila and S. G. Howell and M. E. Kacarab and J. R. Podolske and P. E. Saide and R. Wood},

url = {https://acp.copernicus.org/articles/18/14623/2018/},

doi = {10.5194/acp-18-14623-2018},

year  = {2018},

date = {2018-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {18},

number = {19},

pages = {14623–14636},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1021/acs.est.6b03745,

title = {Estimates of Health Impacts and Radiative Forcing in Winter Haze in Eastern China through Constraints of Surface PM2.5 Predictions},

author = {Meng Gao and Pablo E. Saide and Jinyuan Xin and Yuesi Wang and Zirui Liu and Yuxuan Wang and Zifa Wang and Mariusz Pagowski and Sarath K. Guttikunda and Gregory R. Carmichael},

url = {http://dx.doi.org/10.1021/acs.est.6b03745},

doi = {10.1021/acs.est.6b03745},

year  = {2017},

date = {2017-01-01},

journal = {Environmental Science & Technology},

volume = {51},

number = {4},

pages = {2178-2185},

note = {PMID: 28102073},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-16-1673-2016,

title = {Modeling study of the 2010 regional haze event in the hacknewlineNorth China Plain},

author = {M. Gao and G. R. Carmichael and Y. Wang and P. E. Saide and M. Yu and J. Xin and Z. Liu and Z. Wang},

url = {https://www.atmos-chem-phys.net/16/1673/2016/},

doi = {10.5194/acp-16-1673-2016},

year  = {2016},

date = {2016-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {16},

number = {3},

pages = {1673–1691},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-16-11837-2016,

title = {Response of winter fine particulate matter concentrations to emission 

and meteorology changes in North China},

author = {M. Gao and G. R. Carmichael and P. E. Saide and Z. Lu and M. Yu and D. G. Streets and Z. Wang},

url = {https://www.atmos-chem-phys.net/16/11837/2016/},

doi = {10.5194/acp-16-11837-2016},

year  = {2016},

date = {2016-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {16},

number = {18},

pages = {11837–11851},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{JGRD:JGRD52677,

title = {Air quality forecasting for winter-time PM2.5 episodes occurring in multiple cities in central and southern Chile},

author = {Pablo E. Saide and Marcelo Mena-Carrasco and Sebastian Tolvett and Pablo Hernandez and Gregory R. Carmichael},

url = {http://dx.doi.org/10.1002/2015JD023949},

doi = {10.1002/2015JD023949},

issn = {2169-8996},

year  = {2016},

date = {2016-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {121},

number = {1},

pages = {558–575},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{JGRD:JGRD53270,

title = {Assessment of biomass burning smoke influence on environmental conditions for multiyear tornado outbreaks by combining aerosol-aware microphysics and fire emission constraints},

author = {Pablo E. Saide and Gregory Thompson and Trude Eidhammer and Arlindo M. Silva and R. Bradley Pierce and Gregory R. Carmichael},

url = {http://dx.doi.org/10.1002/2016JD025056},

doi = {10.1002/2016JD025056},

issn = {2169-8996},

year  = {2016},

date = {2016-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {121},

number = {17},

pages = {10,294–10,311},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{JGRD:JGRD53068,

title = {Surface dimming by the 2013 Rim Fire simulated by a sectional aerosol model},

author = {Pengfei Yu and Owen B. Toon and Charles G. Bardeen and Anthony Bucholtz and Karen H. Rosenlof and Pablo E. Saide and Arlindo Da Silva and Luke D. Ziemba and Kenneth L. Thornhill and Jose-Luis Jimenez and Pedro Campuzano-Jost and Joshua P. Schwarz and Anne E. Perring and Karl D. Froyd and N. L. Wagner and Michael J. Mills and Jeffrey S. Reid},

url = {http://dx.doi.org/10.1002/2015JD024702},

doi = {10.1002/2015JD024702},

issn = {2169-8996},

year  = {2016},

date = {2016-01-01},

journal = {Journal of Geophysical Research: Atmospheres},

volume = {121},

number = {12},

pages = {7079–7087},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-15-5325-2015,

title = {Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models},

author = {M. Bocquet and H. Elbern and H. Eskes and M. Hirtl and R. Žabkar and G. R. Carmichael and J. Flemming and A. Inness and M. Pagowski and J. L. Pérez Camaño and P. E. Saide and R. San Jose and M. Sofiev and J. Vira and A. Baklanov and C. Carnevale and G. Grell and C. Seigneur},

url = {https://www.atmos-chem-phys.net/15/5325/2015/},

doi = {10.5194/acp-15-5325-2015},

year  = {2015},

date = {2015-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {15},

number = {10},

pages = {5325–5358},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{GAO2015553,

title = {Health impacts and economic losses assessment of the 2013 severe haze event in Beijing area},

author = {Meng Gao and Sarath K. Guttikunda and Gregory R. Carmichael and Yuesi Wang and Zirui Liu and Charles O. Stanier and Pablo E. Saide and Man Yu},

url = {http://www.sciencedirect.com/science/article/pii/S004896971500008X},

doi = {https://doi.org/10.1016/j.scitotenv.2015.01.005},

issn = {0048-9697},

year  = {2015},

date = {2015-01-01},

journal = {Science of The Total Environment},

volume = {511},

number = {Supplement C},

pages = {553 - 561},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{acp-15-1683-2015,

title = {Source sector and region contributions to BC and PM$_2.5$ in Central Asia},

author = {S. Kulkarni and N. Sobhani and J. P. Miller-Schulze and M. M. Shafer and J. J. Schauer and P. A. Solomon and P. E. Saide and S. N. Spak and Y. F. Cheng and H. A. C. Denier van der Gon and Z. Lu and D. G. Streets and G. Janssens-Maenhout and C. Wiedinmyer and J. Lantz and M. Artamonova and B. Chen and S. Imashev and L. Sverdlik and J. T. Deminter and B. Adhikary and A. D'Allura and C. Wei and G. R. Carmichael},

url = {https://www.atmos-chem-phys.net/15/1683/2015/},

doi = {10.5194/acp-15-1683-2015},

year  = {2015},

date = {2015-01-01},

journal = {Atmospheric Chemistry and Physics},

volume = {15},

number = {4},

pages = {1683–1705},

keywords = {},

pubstate = {published},

tppubtype = {article}

}