Abstract

A method for deriving estimates of long-term acidic deposition over eastern North America based on a limited number of Regional Acid Deposition Model runs has been developed. The main components of this method are the identification of a representative sample of events for model simulation and the aggregation of the deposition totals associated with the events. Meteorological categories, defined according to 3-day progressions of 850-mb wind flow over eastern North America, were used to guide the selection of events. This paper describes how events were selected from the categories and how they were combined (aggregated) to estimate long-term deposition. The effectiveness of the category-based approach was compared against alternate aggregation approaches and it was found to provide the best sample-based estimates of long-term wet sulfate deposition across eastern North America.

Thirty events from the 1982–85 time period were selected using a set of predetermined criteria and aggregated to estimate seasonal and annual SO²⁻ ₄, NO⁻ ₃, and H⁺ deposition at 20 Utility Acid Precipitation Study Program sites. The accuracy of the estimates varied geographically and depending upon whether they were for the annual or seasonal time periods. Over the main area of interest (a smaller 13-site region), the mean rms errors for annual deposition were 10%, 15%, and 12% for sulfate, nitrate, and acidity, respectively. Source–receptor relationships associated with the 30 events were examined for three sites located in Michigan, North Carolina, and upstate New York. It was found that the amount of time that transport was to these areas from the U.S. Midwest (an area of high SO₂ emissions) was represented to within 20%.

Abstract

Running 3-day periods from 1979 to 1985 were categorised into one of 20 meteorological categories. These categories were developed through the cluster analysis of 3-day progressions of 85-kPa wind flow over eastern North America. The purpose for developing the categories was to identify recurring atmospheric transport patterns that were associated with differing amounts of wet sulfate (SO²⁻ ₄) and nitrate (NO⁻ ₃) deposition at a variety of locations in eastern North America. Identification of these patterns was necessary to facilitate the selection of time periods for simulation by the Regional Acid Deposition Model and in the development of a method for estimating long-term acidic deposition over eastern North America from a limited number of model runs. The effectiveness of this method (referred to as the aggregation method) was expected to be dependent on the ability of the categories to separate structure in wet deposition patterns. This paper describes the determination of the 20 meteorological categories and demonstrates that there were differences in their meteorological and chemical behavior and in their frequency of occurrence. Observations of precipitation and wet SO²⁻ ₄ and NO⁻ ₃ deposition from 22 sites in eastern North America and multiple regression models were used to demonstrate that there were statistically significant differences in deposition among categories and that knowledge of meteorological category explained some of the variation in wet deposition. The best statistical correlation, which was based upon precipitation amount, time of year, and meteorological category, explained 35%–83% (28%– 76%) of the observed variation in wet SO²⁻ ₄ (NO⁻ ₃) deposition depending on location. On average, across all sites and for both SO²⁻ ₄ and NO⁻ ₃, knowledge of category accounted for about 4% of the variation. The minimum amount explained by category was 1% and the maximum was 13%.

Abstract

In this paper, the authors present an analysis of correlations between SO₂ emissions and wet SO²⁻ ₄ concentrations over eastern North America that includes adjustments for the impact of meteorological variability. The approach uses multiple-regression models and readily available meteorological information to analyze precipitation chemistry data collected from 1979 to 1986 at six Utility Acid Precipitation Study Program site. On an event-to-event basis, from 25% to 50% of the variation in concentrations, depending on site, was found to be related to meteorology. Precipitation amount, temperature, upwind emissions, and upwind mean lower-tropospheric relative humidity (indicator for upwind precipitation) were related to the natural log of SO²⁻ ₄ concentrations. Inclusion of this information resulted in a decrease in the uncertainty associated with the emission change to concentration relationship at all sites, but the results were inconsistent Year-to-year and season-to-season changes in SO₂ emissions were found to be significantly related (p < 0.033) to variations in event and seasonal concentrations at three of the sites, but not at the other three sites. Possible explanations for this discrepancy are discussed in this paper. When all sites were examined simultaneously, strong statistical correlations (p < 0.007) were found between emissions and concentrations, indicating that SO²⁻ ₄ concentrations decreased in response to seasonal and annual emission changes.

Abstract

In August and September of 2010, measurements of turbulent fluxes and turbulent kinetic energy were made on highways in the Toronto area (Ontario, Canada). In situ turbulence measurements were made with a mobile laboratory while driving on the highway with traffic. Results demonstrate that the turbulent kinetic energy (TKE) spectrum is significantly enhanced on and near the highway by traffic for frequencies above 0.015 Hz. The decay of TKE with distance behind vehicles is well approximated by power-law curves. The strongest increase in TKE is seen while following heavy-duty trucks, primarily for frequencies above 0.7 Hz. From these results, a parameterization of on-road TKE enhancement is developed that is based on vehicle type and traffic-flow rate. TKE with distance downwind of the highway also decays following a power law. The enhancement of roadside TKE is shown to be strongly dependent on traffic flow. The effect of vehicle-induced turbulence on vertical mixing was studied by comparing parameterized TKE enhancement with the typical TKE predictions from the Global Environmental Multiscale weather forecast to predict the potential increase in vertical diffusion that results from highway traffic. It is demonstrated that this increase in TKE by traffic may be locally significant, especially in the early morning.

Abstract

The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.