Jeff McQueen

Assessment of an ensemble of seven real-time ozone forecasts over eastern North America during the summer of 2004

The real-time forecasts of ozone (O 3 ) from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected during July and August of 2004 (53 days) through the Aerometric Information Retrieval Now (AIRNow) network at roughly 340 monitoring stations throughout the eastern United States and southern Canada. One of the first ever real-time ensemble O 3 forecasts, created by combining the seven separate forecasts with equal weighting, is also evaluated in terms of standard statistical measures, threshold statistics, and variance analysis. The ensemble based on the mean of the seven models and the ensemble based on the median are found to have significantly more temporal correlation to the observed daily maximum 1-hour average and maximum 8-hour average O 3 concentrations than any individual model. However, root-mean-square errors (RMSE) and skill scores show that the usefulness of the uncorrected ensembles is limited by positive O 3 biases in all of the AQFMs. The ensembles and AQFM statistical measures are reevaluated using two simple bias correction algorithms for forecasts at each monitor location: subtraction of the mean bias and a multiplicative ratio adjustment, where corrections are based on the full 53 days of available comparisons. The impact the two bias correction techniques have on RMSE, threshold statistics, and temporal variance is presented. For the threshold statistics a preferred bias correction technique is found to be model dependent and related to whether the model overpredicts or underpredicts observed temporal O 3 variance. All statistical measures of the ensemble mean forecast, and particularly the bias-corrected ensemble forecast, are found to be insensitive to the results of any particular model. The higher correlation coefficients, low RMSE, and better threshold statistics for the ensembles compared to any individual model point to their preference as a real-time O 3 forecast.

Meteorological Research Needs for Improved Air Quality Forecasting Report of the 11th Prospectus Development Team of the U.S. Weather Research Program

Abstract The U.S. Weather Research Program convenes expert working groups on a one-time basis to identify critical research needs in various problem areas. The most recent expert working group was charged to “identify and delineate critical meteorological research issues related to the prediction of air quality.” In this context, “prediction” is denoted as “forecasting” and includes the depiction and communication of the present chemical state of the atmosphere, extrapolation or nowcasting, and numerical prediction and chemical evolution on time scales up to several days. Emphasis is on the meteorological aspects of air quality. The problem of air quality forecasting is different in many ways from the problem of weather forecasting. The latter typically is focused on prediction of severe, adverse weather conditions, while the meteorology of adverse air quality conditions frequently is associated with benign weather. Boundary layer structure and wind direction are perhaps the two most poorly determined met...

Using National Air Quality Forecast Guidance to Develop Local Air Quality Index Forecasts

The National Air Quality Forecast Capability (NAQFC) currently provides next-day forecasts of ozone concentrations over the contiguous United States. It was developed collaboratively by NOAA and Environmental Protection Agency (EPA) in order to provide state and local agencies, as well as the general public, air quality forecast guidance. As part of the development process, the NAQFC has been evaluated utilizing strict monitor-to-gridcell matching criteria, and discrete-type statistics of forecast concentrations. While such an evaluation is important to the developers, it is equally, if not more important, to evaluate the performance using the same protocol as the models intended application. Accordingly, the purpose of this article is to demonstrate the efficacy of the NAQFC from the perspective of a local forecaster, thereby promoting its use. Such an approach has required the development of a new evaluation protocol: one that examines the ability of the NAQFC to forecast values of the EPAs Air Qualit...

Impact of Domain Size on Modeled Ozone Forecast for the Northeastern United States

Abstract This study investigates the impact of model domain extent and the specification of lateral boundary conditions on the forecast quality of air pollution constituents in a specific region of interest. A developmental version of the national Air Quality Forecast System (AQFS) has been used in this study. The AQFS is based on the NWS/NCEP Eta Model (recently renamed the North American Mesoscale Model) coupled with the U.S. Environmental Protection Agency Community Multiscale Air Quality (CMAQ) model. This coupled Eta–CMAQ modeling system provided experimental air quality forecasts for the northeastern region of the United States during the summers of 2003 and 2004. The initial forecast over the northeastern United States was approved for operational deployment in September 2004. The AQFS will provide forecast coverage for the entire United States in the near future. In a continuing program of phased development to extend the geographical coverage of the forecast, the developmental version of AQFS has...

Evaluating the Vertical Distribution of Ozone and Its Relationship to Pollution Events in Air Quality Models Using Satellite Data

Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture the distribution of ozone in the mid- and upper troposphere, but it is unclear how this shortcoming relates to their ability to simulate surface ozone. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and a new joint product from TES and the Ozone Monitoring Instrument along with ozonesonde measurements and EPA AirNow ground station ozone data to examine air quality events during August 2006 in the Community Multi-Scale Air Quality (CMAQ) and National Air Quality Forecast Capability (NAQFC) models. We present both aggregated statistics and case-study analyses with the goal of assessing the relationship between the models’ ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone. We find that the models lack the mid-tropospheric ozone variability seen in TES and the ozonesonde data, and discuss future work to determine the conditions under which this variability appears to be important for surface air quality.

An Assessment of a Real-Time Analysis and Its Impact on Dispersion Modeling

The height of the Planetary Boundary Layer (PBL) is an important quantity for certain applications such as dispersion modeling. A dedicated two-dimensional PBL height analysis has been developed as an additional component of NCEP’s Real-Time Mesoscale Analysis. As for other meteorological analysis applications, the quality of the output is dependent on the quality of the input, including the observation. Here we assess the quality and potential for use in the PBL height analysis of a series of candidate observations, including Radiosonde Observations (RAOBS), Aircraft Communications Addressing and Reporting System (ACARS), Cooperative Agency Profilers (CAP), COSMIC satellite Radio Occultation and NWS Next-Rad radar reflectivities. The quality is assessed both by physical plausibility of the measurements and by comparison of the observations and the resulting analysis with independent observations not used in the analysis.

Incremental Development of Air Quality Forecasting System with Off-Line/On-Line Capability: Coupling CMAQ to NCEP National Mesoscale Model

The National Air Quality Forecast Capability (NAQFC) is based on the EPA Community Multiscale Air Quality (CMAQ) model driven by meteorological data from the NOAA North American Mesoscale (NAM) Non-hydrostatic Meso-scale Model (NMM). Currently, NMM meteorological data on Arakawa E-grid are interpolated on a CMAQ’s Arakawa C-grid using the processors PRODGEN and PREMAQ to handle map-projection transform, vertical layer collapsing, and other emission and meteorological data feed issues. The FY11 pre-implementation version of NAM has undergone significant changes in the vertical layering, horizontal grid projection and improved science components for its FY11 upcoming major upgrade release. This provides an opportunity to improve the coupling methodology between NMM and CMAQ that reduces uncertainties both in the meteorological and emission inputs for the off-line air quality modeling and helps development of on-line NMM-CMAQ version. Three major tasks are needed to achieve a tighter coupling between them: (1) Adapt to NAM’s vertical hybrid pressure and grid structure; (2) Change CMAQ to use the same rotated latitude longitude B staggered horizontal grid structure as NAM, (3) Modify emission model to provide generic inputs for the B staggered grid and hybrid vertical structure of NAM. The first task achieves consistent matching of dynamics between the two systems, despite the possible necessity of layer-collapsing to fit within operational time-lines. The second task removes unnecessary interpolation of meteorology data for air quality simulations. The third task involves modification of the U.S. EPA Sparse Matrix Object Kernel Emission (SMOKE) model to handle the staggered B grid. At this time only the first of these three steps has been accomplished, and the test result from this test focusing on the selected test period has been compared to that produced by the operational NAQFC. Further work with all these three modifications concurrently in place is underway.