Sara A. Michelson

Observed and WRF-Simulated Low-Level Winds in a High-Ozone Episode during the Central California Ozone Study

Abstract A case study is carried out for the 29 July–3 August 2000 episode of the Central California Ozone Study (CCOS), a typical summertime high-ozone event in the Central Valley of California. The focus of the study is on the low-level winds that control the transport and dispersion of pollutants in the Central Valley. An analysis of surface and wind profiler observations from the CCOS field experiment indicates a number of important low-level flows in the Central Valley: 1) the incoming low-level marine airflow through the Carquinez Strait into the Sacramento River delta, 2) the diurnal cycle of upslope–downslope flows, 3) the up- and down-valley flow in the Sacramento Valley, 4) the nocturnal low-level jet in the San Joaquin Valley, and 5) the orographically induced mesoscale eddies (the Fresno and Schultz eddies). A numerical simulation using the advanced research version of the Weather Research and Forecasting Model (WRF) reproduces the overall pattern of the observed low-level flows. The physical ...

Seasonal versus episodic performance evaluation for an Eulerian photochemical air quality model

Seasonal versus Episodic Performance Evaluation for an Eulerian Photochemical Air Quality Model Ling Jin, Nancy J Brown Lawrence Berkeley National Laboratory, Berkeley, CA 94720 Robert A Harley University of California, Berkeley, CA 94720 Jian-Wen Bao, Sara A Michelson, James M Wilczak National Oceanographic and Atmospheric Administration, Boulder, CO 80305 Corresponding author: Nancy J Brown, njbrown@lbl.gov, 510-486-4241 Abstract This study presents detailed evaluation of the seasonal and episodic performance of the Community Multiscale Air Quality (CMAQ) modeling system applied to simulate air quality at a fine grid spacing (4 km horizontal resolution) in central California, where ozone air pollution problems are severe. A rich aerometric data base collected during the summer 2000 Central California Ozone Study (CCOS) is used to prepare model inputs and to evaluate meteorological simulations and chemical outputs. We examine both temporal and spatial behaviors of ozone predictions. We highlight synoptically-driven high-ozone events (exemplified by the four Intensive Operating Periods, IOPs) for evaluating both meteorological inputs and chemical out puts (ozone and its precursors) and compare them to the summer average. For most of the summer days, cross-domain normalized gross errors are less than 25% for modeled hourly ozone, and normalized biases are between ±15% for both hourly and peak (1 h and 8 h) ozone. The domain-wide aggregated metrics indicate similar performance between the IOPs and the whole summer with respect to predicted ozone and its precursors. Episode-to-episode differences in ozone predictions are more pronounced at a subregional level. The model performs consistently better in the San Joaquin Valley than other air basins, and episodic ozone predictions there are similar to the summer average. Poorer model performance (normalized peak ozone biases 15%) is found in the Sacramento Valley and the Bay Area and is most noticeable in episodes that are subject to the largest uncertainties in meteorological fields (wind directions in the Sacramento Valley and timing and strength of onshore flow in the Bay Area) within the boundary layer.

Evaluation of the Summertime Low-Level Winds Simulated by MM5 in the Central Valley of California

Abstract A season-long set of 5-day simulations between 1200 UTC 1 June and 1200 UTC 30 September 2000 are evaluated using the observations taken during the Central California Ozone Study (CCOS) 2000 experiment. The simulations are carried out using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), which is widely used for air-quality simulations and control planning. The evaluation results strongly indicate that the model-simulated low-level winds in California’s Central Valley are biased in speed and direction: the simulated winds tend to have a stronger northwesterly component than observed. This bias is related to the difference in the observed and simulated large-scale, upper-level flows. The model simulations also show a bias in the height of the daytime atmospheric boundary layer (ABL), particularly in the northern and southern Central Valley. There is evidence to suggest that this bias in the daytime ABL height is not only associated with the large-scale, upper-level b...

Use of Remote Sensors in Air Quality Monitoring and Prediction

Air quality is a highly interdisciplinary problem dependent on both chemical and meteorological processes. The investigation of atmospheric pollution requires information about the types of emitted chemical compounds, their concentrations, their mutual interaction under different ambient conditions, and finally about their transport and diffusion into the atmosphere. This chapter introduces the effects of meteorology on air quality and the use of meteorological data from remote sensors in air quality monitoring and prediction. The change in air quality over the course of a diurnal cycle is described, explaining the role of atmospheric boundary layer and turbulence motion. Because of the need to measure the strength of the vertical mixing and the depth through which it occurs, as well as the vertical profile of wind speed and direction throughout the lowest several kilometers of the atmosphere, remote sensors, such as lidars and wind profiling radars, are demonstrated to be extremely valuable for assessing and predicting air quality. Few examples of air quality experiments are presented to demonstrate how remote sensors can lead to new insights on the local meteorology control on air pollutant concentrations and the benefit of meteorological data assimilation in air quality prediction.