Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Kumar, Rajesh; Bhardwaj, Piyush; Pfister, Gabriele; Drews, Carl; Honomichl, Shawn; D’Attilo, Garth

doi:10.3390/atmos12030302

Cited by 9 publications

(10 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The representativeness of Platteville monitoring for the O&G fields was demonstrated with the NOAA hybrid single‐particle lagrangian integrated trajectory (HYSPLIT) back trajectories for 2018 (Rolph et al., 2017; Stein et al., 2015) as well as plots of ethane concentrations and winds from the experimental forecasting system that is run by the National Center for Atmospheric Research (NCAR) and based on the Weather Research and Forecasting (WRF) model with chemistry (WRF‐Chem) (Kumar et al., 2021). NCAR’s WRF‐Chem is a quasi‐operational regional air quality forecasting system for the contiguous United States developed to support field campaigns, air quality forecasting, and research.…”

Section: Data Sources and Methodsmentioning

confidence: 99%

Downward Trend in Methane Detected in a Northern Colorado Oil and Gas Production Region Using AIRS Satellite Data

Reddy

Taylor

2022

Earth and Space Science

View full text Add to dashboard Cite

The oil and gas (O&G) sector is estimated to be the largest contributor to anthropogenic methane (CH4) emissions in Colorado. Since 2004, the State of Colorado has implemented multiple regulations to significantly reduce emissions from the O&G sector. The Denver‐Julesburg Basin (DJ Basin) is a significant O&G producing region in northern Colorado, and O&G production here has steadily increased over the last decade. To assess CH4 trends in Northern Colorado, we selected CH4 retrievals from the NASA Atmospheric Infrared Sounder (AIRS) instrument for 2003–2020. The study grid cell includes Denver, Boulder, and much of the dense O&G production in the DJ Basin. We computed mean June‐August ascending node AIRS 700 hPa CH4 for each year and subtracted mean June–August CH4 sampled at NOAA's Niwot Ridge (NWR) station, a high‐altitude background site. Differences represent estimated enhancement over background. Linear regression shows an annual change of −2.84 ppb ± 0.8 ppb from 2012 to 2020 (R2 0.90) and an estimated reduction of 56% for 2012–2020, despite substantial increases in O&G production. Local CH4 enhancement is strongly correlated with surface measurements of ethane at Platteville which is in the center of the O&G fields (correlation coefficient 0.96), and this is evidence that reductions in O&G emissions are driving reductions in CH4. We conclude that AIRS CH4 can be used to measure the efficacy of emissions control programs in this region and that regulatory requirements are having an effect.

show abstract

Section: Data Sources and Methodsmentioning

confidence: 99%

Downward Trend in Methane Detected in a Northern Colorado Oil and Gas Production Region Using AIRS Satellite Data

Reddy

Taylor

2022

Earth and Space Science

View full text Add to dashboard Cite

show abstract

“…Wildfire emissions, thermal, and speciation characteristics are determined in near-real time by the US Forest Service X. Ye et al: Evaluation and intercomparison of wildfire smoke forecasts BlueSky smoke emission package (Larkin et al, 2009) and the NOAA/NESDIS Hazard Mapping System (HMS) for fire location and strength (Ruminski and Kondragunta, 2006). The BlueSky wildfire heat flux was used in the Briggs equation (Briggs, 1975) to determine smoke plume injection heights.…”

Section: Naqfcmentioning

confidence: 99%

Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire

Arab

Ahmadov

et al. 2021

Atmos. Chem. Phys.

Self Cite

View full text Add to dashboard Cite

Abstract. Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

show abstract

“…It uses the US EPA National Emission Inventory (NEI) 2014v2 and correction factors based on satellites to account for trends in NO x emissions (Tong et al, 2015). Wildfire emissions, thermal, and speciation characteristics are determined in near-real time by the US Forest Service BlueSky smoke emission package (Larkin et al, 2009) and the NOAA/NESDIS Hazard Mapping System (HMS) for fire location and strength (Ruminski and Kondragunta, 2006). The BlueSky wildfire heat flux was used in the Briggs equation (Briggs, 1975) to determine smoke plume injection heights.…”

Section: Naqfcmentioning

confidence: 99%

Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire

Ye¹,

Arab²,

Ahmadov³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from twelve state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, the U.S., August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within one day are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by FRP-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019 mainly over the transported smoke plumes, owing to the underestimated emissions on the 7th. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center’s Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper with the day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported one-day-old smoke. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

show abstract

Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Cited by 9 publications

References 33 publications

Downward Trend in Methane Detected in a Northern Colorado Oil and Gas Production Region Using AIRS Satellite Data

Downward Trend in Methane Detected in a Northern Colorado Oil and Gas Production Region Using AIRS Satellite Data

Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire

Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire

Contact Info

Product

Resources

About