ALBERT

Description: The impacts of transported background (TBG) pollutants on Western US ozone (O3) distributions in summer 2008 are studied using the multi-scale Sulfur Transport and dEposition Modeling system. Forward sensitivity simulations show that TBG extensively affect Western US surface O3, and can contribute to 〉50% of the total O3, varying among different geographical regions and land types. The stratospheric O3 impacts are weak. Ozone is the major contributor to surfaceO3 among the TBG pollutants, and TBG peroxyacetyl nitrate is the most important O3 precursor species. Compared to monthly mean daily maximum 8-h average O3, the secondary standard metric "W126 monthly index" shows larger responses to TBG perturbations and stronger non-linearity to the size of perturbations. Overall the model-estimated TBG impacts negatively correlate to the vertical resolution and positively correlate to the horizontal resolution. The estimated TBG impacts weakly depend on the uncertainties in US anthropogenic emissions. Ozone sources differ at three sites spanning ~10° in latitude. Mt. Bachelor (MBO) and Trinidad Head (THD) O3 are strongly affected by TBG, and occasionally by US emissions, while South Coast (SC) O3 is strongly affected by local emissions. The probabilities of airmasses originating from MBO (2.7 km) and THD (2.5 km) entraining into the boundary layer reach daily maxima of 66% and 34% at ~3:00 p.m. PDT, respectively, and stay above 50% during 9:00 a.m.–4:00 p.m. for those originating from SC (1.5 km). Receptor-based adjoint sensitivity analysis demonstrates the connection between the surface O3 and O3 aloft (at ~1–4 km) at these sites 1–2 days earlier. Assimilation of the surface in-situ measurements significantly reduced (~5 ppb in average, up to ~17 ppb) the modeled surface O3 errors during a long-range transport episode, and is useful for estimating the upper-limits of uncertainties in satellite retrievals (in this case 5–20% and 20–30% for Tropospheric Emission Spectrometer (TES) and Ozone Monitoring Instrument (OMI) O3 profiles, respectively). Satellite observations identified this transport event, but assimilation of the existing O3 vertical profiles from TES, OMI and THD sonde in this case did not efficiently improve the O3 distributions except near the sampling locations, due to their limited spatiotemporal resolution and possible uncertainties.

Description: The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) modeling system. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO2) observations are used to evaluate the experimental predictions in 2010. It is found that both ozone and NO2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO2. For both species the overpredictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO2 in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO2 biases in August show distinctively high values in the Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO2. Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO2, the morning predictions agree with the AQS observations reasonably well, but nighttime concentrations are overpredicted by around 100%.

Description: The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) Modeling System. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO2) observations are used to evaluate the experimental predictions in 2010, with a view towards their improvement. It is found that both ozone and NO2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 ppbv and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO2. For both species the over-predictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO2 in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO2 biases in July and August show distinctively high values in Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO2. Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO2, the morning predictions agree with the AQS observations reasonably well, but night-time concentrations are over-predicted by around 100%. Based on the analysis presented here, experimental ozone prediction system was updated for summer 2012.

Description: Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error and thus the MAE would be a better metric for that purpose. Their paper has been widely cited and may have influenced many researchers in choosing MAE when presenting their model evaluation statistics. However, we contend that the proposed avoidance of RMSE and the use of MAE is not the solution to the problem. In this technical note, we demonstrate that the RMSE is not ambiguous in its meaning, contrary to what was claimed by Willmott et al. (2009). The RMSE is more appropriate to represent model performance than the MAE when the error distribution is expected to be Gaussian. In addition, we show that the RMSE satisfies the triangle inequality requirement for a distance metric.

Description: Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error, and thus the MAE would be a better metric for that purpose. While some concerns over using RMSE raised by Willmott and Matsuura (2005) and Willmott et al. (2009) are valid, the proposed avoidance of RMSE in favor of MAE is not the solution. Citing the aforementioned papers, many researchers chose MAE over RMSE to present their model evaluation statistics when presenting or adding the RMSE measures could be more beneficial. In this technical note, we demonstrate that the RMSE is not ambiguous in its meaning, contrary to what was claimed by Willmott et al. (2009). The RMSE is more appropriate to represent model performance than the MAE when the error distribution is expected to be Gaussian. In addition, we show that the RMSE satisfies the triangle inequality requirement for a distance metric, whereas Willmott et al. (2009) indicated that the sums-of-squares-based statistics do not satisfy this rule. In the end, we discussed some circumstances where using the RMSE will be more beneficial. However, we do not contend that the RMSE is superior over the MAE. Instead, a combination of metrics, including but certainly not limited to RMSEs and MAEs, are often required to assess model performance.

Description: The impacts of transported background (TBG) pollutants on western US ozone (O3) distributions in summer 2008 are studied using the multi-scale Sulfur Transport and dEposition Modeling system. Forward sensitivity simulations show that TBG contributes ~30–35 ppb to the surface Monthly mean Daily maximum 8-h Average O3 (MDA8) over Pacific Southwest (US Environmental Protection Agency (EPA) Region 9, including California, Nevada and Arizona) and Pacific Northwest (EPA Region 10, including Washington, Oregon and Idaho), and ~10–17 ppm-h to the secondary standard metric "W126 monthly index" over EPA Region 9 and ~3–4 ppm-h over Region 10. The strongest TBG impacts on W126 occur over the grass/shrub-covered regions. Among TBG pollutants, O3 is the major contributor to surface O3, while peroxyacetyl nitrate is the most important O3 precursor species. W126 shows larger responses than MDA8 to perturbations in TBG and stronger non-linearity to the magnitude of perturbations. The TBG impacts on both metrics overall negatively correlate to model vertical resolution and positively correlate to the horizontal resolution. The mechanisms that determine TBG contributions and their variation are analyzed using trajectories and the receptor-based adjoint sensitivity analysis, which demonstrate the connection between the surface O3 and O3 aloft (at ~1–4 km) 1–2 days earlier. The probabilities of airmasses originating from Mt. Bachelor (2.7 km) and 2.5 km above Trinidad Head (THD) entraining into the boundary layer reach daily maxima of 66% and 34% at ~03:00 p.m. Pacific Daylight Time (PDT), respectively, and stay above 50% during 09:00 a.m.–04:00 p.m. PDT for those originating 1.5 km above California's South Coast. Assimilation of the surface in-situ measurements significantly reduced the errors in the modeled surface O3 during a long-range transport episode by ~5 ppb on average (up to ~17 ppb) and increased the estimated TBG contributions by ~3 ppb. Available O3 vertical profiles from Tropospheric Emission Spectrometer (TES), Ozone Monitoring Instrument (OMI) and THD sonde identified this transport event, but assimilation of these observations in this case did not efficiently improve the O3 distributions except near the sampling locations, due to their limited spatiotemporal resolution and/or possible uncertainties.