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REGIONAL DOWNSCALING for AIR QUALITY ASSESSMENT a Reasonable Proposition?

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REGIONAL DOWNSCALING for AIR QUALITY ASSESSMENT a Reasonable Proposition? REGIONAL DOWNSCALING FOR AIR QUALITY ASSESSMENT A Reasonable Proposition? BY WILLIAM I. GUSTAFSON JR. AND L. RUBY LEUNG Dynamical downscaling promises improved firiescale meteorological fields, but is the technique providing useful regional climate information for air quality assessment? ^ ince the development of the first regional climate application of regional downscaling has been the \ model (Dickinson et al. 1989), dynamical down- assessment of potential changes in air quality in a J scaling has been applied to provide regional future climate (Forkel and Knoche 2006; Hogrefe climate information for assessing climate change et al. 2004; Leung and Gustafson 2005; Steiner et al. impacts. In dynamical downscaling, regional-scale 2006). Air quality for a given region depends upon models are driven by large-scale boundary condi- pollutant emissions, chemical reactions, and meteo- tions, including winds, temperature, water vapor, rology, including transport and mixing. However, and sea surface temperature, from global models or emissions are relatively consistent while weather an analysis product to simulate atmospheric circula- conditions change from day to day, ultimately deter- tion for a region at higher spatial resolution (Giorgi mining the impact of the emissions on the air quality. and Mearns 1999; Leung et al. 2003a). While most Given that air quality depends heavily upon meteoro- studies focused on the assessment of water resources, logical conditions and these conditions may change agriculture, and ecosystems, more recently a new in the coming decades, a valid question is "How will climate change alter air quality?" As models become more sophisticated and interactive, the alternative AFFILIATIONS: GUSTAFSON AND LEUNG—Atmospheric Science question can also be asked, "How will air quality alter and Global Change Division, Pacific Northwest National climate?" Our ability to address these questions relies Laboratory, Richland, Washington critically on the ability of climate models to simulate CORRESPONDING AUTHOR: Dr. William I. Gustafson Jr., Pa- the meteorological conditions needed to realistically cific Northwest National Laboratory, Post Office Box 999, MSIN simulate air quality. Because of the nonlinear nature K9-30, Richland, WA 99352 E-mail: [email protected] of atmospheric chemistry and its dependence on difficult-to-model variables, such as precipitation The abstract for this article can be found in this issue, following the and the planetary boundary layer (PBL) height, table of contents. biases in variables considered acceptable for other DON 0.1175/BAMS-88-8-I2I5 downscaling applications may not be appropriate In final form 6 March 2007 ©2007 American Meteorological Society for this new application. An additional challenge in air quality assessment is the required knowledge of AMERICAN METEOROLOGICAL SOCIETY AUGUST 2007 BAFft I 1215 Unauthenticated | Downloaded 10/10/21 03:15 PM UTC the three-dimensional structures of the atmosphere, rology in the control and altered climate is essential. which are not needed for most other assessments. When using statistical models, it maybe possible to use Two conceptual frameworks exist for predicting a coarse representation generated with a global circula- air quality changes in an altered climate. The first is tion model (GCM) to characterize the weather regimes. to statistically identify weather conditions or regimes In the explicit modeling approach, high-resolution conducive to particular air quality events and then gridded meteorological data are needed to represent to infer changes in air quality based on how weather small-scale weather events and to drive air quality changes in the new climate. Examples of weather models. Thus, assessing future air quality at city and connections to high ozone include the following: a state scales requires dynamical downscaling. study of the Lake Michigan lake breeze (Lennartson Historically, regional modeling for air quality and Schwartz 2002); the study by Berman et al. assessment involves short-duration case studies aimed (1999) showing a connection between lower ventila- at advancing our understanding of meteorological tion coefficients, the product of the boundary layer and chemical processes, and their interactions. The height and the boundary layer wind speed, and high- short duration keeps the simulations in the realm of ozone days in New England; a connection between weather, as opposed to climate. In this type of study, recirculating air patterns and ozone in Atlanta observations can be used to constrain the simulation (John and Chameides 1997); and a connection to produce more realistic features, such as land-sea between anticyclones and warm advection in Athens breezes, that are important for air quality assessment (Kassomenos et al. 1995). Two difficulties exist for (Jiang and Fast 2004). Without data assimilation, extending these statistical relationships into the simulations beyond 1-2 weeks drift away from real future. First, connections between weather and air weather sequences and must be treated in a climato- quality are highly nonlinear and depend on multiple logical sense using simulations over much longer time variables in a complex manner; statistical relation- periods. To assess climate change impacts, at least two ships derived under the current climate may not hold simulations must be performed for the past/current when the climate changes. Second, incorporating and future climate conditions. Because no observa- nonweather influences, such as increased anthro- tions exist for the future climate, both simulations pogenic emissions, is not trivial with this method must be performed in a free-running mode with no because the nonlinearity of atmospheric chemistry observational constraints to allow for a meaningful makes it either difficult or impossible to separate comparison of past/current and future climate. The weather and nonweather effects. error structures of short- and long-term simulations To circumvent the nonlinearity problem, an alter- are related, but can differ significantly as a result of native methodology for predicting air quality changes complex feedback processes that play an important is to utilize air quality models using the meteoro- role in long-term simulations. logical conditions found in the control and altered This article investigates regional climate simula- climate. To date, this has been done with different tion skill relevant to air quality assessment. Our goal models, ranging from simple Lagrangian chemistry is to understand how errors in the regional climate transport models (LCTM) to sophisticated regulatory simulations may introduce uncertainty in air quality models. For example, Mayerhofer et al. (2002) used a assessment. No attempts are made in this paper to one-layer LCTM to study sulfur and nitrogen depo- assess air quality simulations driven by the regional sition in Europe for a future climate. Hogrefe et al. climate simulations. We present a comparison of two (2004) used a more thorough approach by running downscaled atmospheric simulations—one driven by the Community Multiscale Air Quality Model a GCM control simulation and the other driven by (CMAQ) coupled with weather fields generated by a global reanalysis—of present-day climate against the fifth-generation Pennsylvania State University observations to investigate how well meteorological (PSU)-National Center for Atmospheric Research conditions important for air quality assessment can (NCAR) Mesoscale Model (MM5) (Grell et al. 1995) be simulated by regional climate models (RCMs). to study changes in summer ozone episodes over Differences between these runs highlight the differ- the eastern United States. Though computationally ence between using a free-running GCM versus an expensive, this methodology can address concurrent observationally constrained model for deriving high- changes in climate and emissions with its physically resolution meteorological information. The readers based approach. are referred to Efthimios et al. 2007 for an evaluation Whether using statistics or explicitly modeling air of air quality simulations using the GCM-driven quality changes, an accurate representation of meteo- downscaled simulation described in this study. 1216 I BAF15- AUGUST 2007 Unauthenticated | Downloaded 10/10/21 03:15 PM UTC MODEL AND DATASET DESCRIPTIONS. warm-season climate remains a significant challenge Mode/ description and simulations. The simulations (e.g., Gutowski et al. 2004; Liang et al. 2004b), and presented in this article were made using MM5 (Grell the use of GCM boundary conditions can introduce et al. 1995). This model, with some modifications additional errors in the regional simulations. described by Leung et al. (2003b), has been applied Two decade-long model runs of present-day to the western United States and found to realistically climate are presented for the United States. The first simulate many aspects of the hydroclimate domi- uses lateral boundary conditions and sea surface nated by the orographic effects and cold-season temperatures derived from a Goddard Institute for processes of that region. However, simulating the Space Studies (GISS) GCM simulation and is referred NONLINEARITY OF ATMOSPHERIC OZONE PRODUCTION nterplay between instantaneous trace gas concentrations, surface emissions, and meteorology leads to strong nonlineari- ties for atmospheric ozone chemistry. While the only significant ozone-forming reaction in the troposphere is the combi- nation of atomic oxygen
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