87th AMS Annual Meeting

Wednesday, 17 January 2007: 9:45 AM
Examining the sensitivity of meteorological and chemical predictions to explicit microphysics schemes
212A (Henry B. Gonzalez Convention Center)
Ashley N. Queen, North Carolina State Univ., Raleigh, NC; and Y. Zhang
Poster PDF (31.3 kB)
Meteorological models currently included in 3-D air quality models (AQMs) offer options to include different model physics. In this study, different explicit microphysics schemes (e.g., Reisner 1 (mixed-phase), Reisner 2 (mixed-phase with graupel), and Dudhia (simple ice)) are applied to the Fifth Generation National Center for Atmospheric Research/Pennsylvania State University (NCAR/PSU) Mesoscale Model (MM5)/Community Multiscale Air Quality (CMAQ) modeling system for two one-month simulation periods (August and December 2002). MM5/CMAQ simulations are conducted with a 4-km horizontal grid spacing on a domain covering most of North Carolina and portions of surrounding states. The results from these simulations are used to examine the impacts of the different explicit microphysics schemes on both meteorological (e.g., precipitation) and chemical (e.g., concentrations and wet deposition amounts of NH4+, NO3-, and SO42-) predictions.

A preliminary evaluation of meteorological predictions shows that during August, the simulation with the Reisner 1 scheme produces the largest precipitation amounts while that with the Dudhia scheme produces the smallest amount. All three simulations underpredict precipitation for August at the Automated Surface Observation Systems (ASOS) sites (NMBs of -35.2% (Reisner 1), -35.3% (Reisner 2), and -35.6% (Dudhia)), while underpredictions occur for simulations with the Reisner 2 and Dudhia schemes (NMBs of -2.8% and -14.3%, respectively) but overpredictions occur for the simulation with the Reisner 1 (NMB of 40.9%) at the National Acid Deposition Program (NADP) sites. During December, all three simulations underpredict precipitation for both the ASOS and NADP networks, with the largest underpredictions by the Reisner 1 simulation (NMBs of -14.7% and -22.8% at ASOS and NADP sites, respectively). The predicted concentrations of PM species from all three schemes are being compared with observations from the Clean Air Status and Trends Network (CASTNet), the Speciated Trends Network (STN), and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network, while wet deposition predictions are being compared with observations from the NADP network. For example, during August the Reisner 1 and Reisner 2 predictions of NH4+, SO42-, and NO3- concentrations are very similar, with NMBs ranging from -37.8 to -24.4%, -78.4 to 35.6%, and -29.7 to -12.3%, respectively across the three networks. The NMBs for their corresponding wet deposition amounts range from 36.8 to 45.3%, -36.9 to -35.2%, and 88.1 to 90.1%, respectively. Analyses of spatial distributions show that the predicted precipitation generally correlates with wet deposition and anticorrelates with PM concentrations (resulting from more pollutant scavenging by increased precipitation). However, comparisons between the Reisner 1 and Reisner 2 simulations show that during periods when no difference in predicted precipitation occurs, some differences in predicted PM concentrations still exist. For example, on August 12, the maximum absolute differences of simulated PM concentrations range from 1.9 to 3.7 μg m-3, 0.2 to 0.4 μg m-3, and 2.8 to 14.2 μg m-3 for NH4+, NO3-, and SO42-, respectively). While this may be attributable to difference in timing and/or location of precipitation events and associated liquid contents, it may also indicate other impacts of the microphysics scheme not directly attributed to precipitation scavenging. These impacts may include differences in the temperature, cloud liquid contents, and water vapor mixing ratios, all of which may impact PM concentrations because of their influences on formation, transformation, and removal mechanisms. A more complete analysis of the Reisner 1, Reisner 2, and Dudhia simulations is being completed to further examine and characterize the impacts of the MM5 explicit microphysics on both meteorological and chemical predictions.

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