Stephen F. Mueller

Tests of models of cloudwater deposition to forest canopies using artificial and living collectors

Mechanistic cloud deposition models are very useful in the routine quantification of cloudwater deposition to forest canopies. In order to test, in a natural field situation, several assumptions in these models, a passive string cloudwater collector, a small artificial tree, and a living Norway spruce were exposed to cloudwater on a raised platform at the summit (elevation, 1686 m) of Whitetop Mountain, Virginia over a 5 month period. Cloudwater collection rates by these three collectors were used to examine relationships between these rates and measured values for two important meteorological variables in the models, liquid water content and wind speed, the product of which is the horizontal cloudwater flux. Collection rates for all three collectors were predicted moderately well by horizontal cloudwater flux (R2 ranged from 0.54 to 0.73; p<0.0001) across all hours of observation, but were least strongly related when liquid water content was low, probably because of various measurement uncertainties under this condition. For all three collectors, simple linear regressions using the horizontal water flux to predict collection rates were not appreciably improved by inclusion of a cloudwater collection efficiency term or by conversion to binomial or curvilinear models. Cloudwater collection efficiency for all three collectors was related to the logarithm of horizontal water flux, as predicted by the models, only when this relationship was analyzed within individual cloud events. Between individual cloud events, collection efficiency varied across a wide range (0.12–0.50 for the spruce tree), with efficiencies much higher during events of short duration. Cloudwater collection efficiency was often lower than predicted by cloud deposition models, possibly because the models use wind speed measurements which do not take into account reductions in wind speed occurring within needle clusters on branches. Collection rates for all three collectors correlated highly with each other (R2 ranged from 0.72 to 0.88; p<0.0001), as well as with a mature red spruce canopy. It was concluded that either the string collector or an artificial tree such as the one used in this study would serve as a good surrogate collector for living spruce tree crowns.

Contributions of natural emissions to ozone and PM2.5 as simulated by the Community Multiscale Air Quality (CMAQ) model.

The relative roles of natural and anthropogenic sources in determining ozone and fine particle concentrations over the continental United States (U.S.) are investigated using an expanded emissions inventory of natural sources and an updated version of the Community Multiscale Air Quality (CMAQ) model. Various 12-month CMAQ simulations for the year 2002 using different sets of input emissions data are combined to delineate the contributions of background pollutants (i.e., model boundary conditions), natural emissions, anthropogenic emissions, as well as the specific impacts of lightning and wildfires. Results are compared with observations and previous air quality model simulations. Wildfires and lightning are both identified as contributing significantly to ozone levels with lightning NO(x) adding as much as 25-30 ppbV (or up to about 50%) to surface 8-h average natural O(3) mixing ratios in the southeastern U.S. Simulated wildfire emissions added more than 50 ppbV (in some cases >90%) to 8-h natural O(3) at several locations in the west. Modeling also indicates that natural emissions (including biogenic, oceanic, geogenic and fires) contributed ≤ 40% to the annual average of total simulated fine particle mass over the eastern two-thirds of the U.S. and >40% across most of the western U.S. Biogenic emissions are the dominant source of particulate mass over the entire U.S. and wildfire emissions are secondary. Averaged over the entire modeling domain, background and natural ozone are dominant with anthropogenically derived ozone contributing up to a third of the total only during summer. Background contributions to fine particle levels are relatively insignificant in comparison. Model results are also contrasted with the U.S. Environmental Protection Agency (EPA) default values for natural light scattering particle concentrations to be used for regional haze regulatory decision-making. Regional differences in EPA guidance are not supported by the modeling and EPA uncertainty estimates for default values are far smaller than the modeled variability in natural particle concentrations.

Characterization of ambient ozone levels in the Great Smoky Mountains National Park

Abstract Ambient ozone data collected at two sites in the Great Smoky Mountains National Park (GSMNP) are summarized and compared with data from an urban and a low-elevation rural site. The ozone climatology in the park is found to be similar to that of other remote sites in the southern Appalachian Mountain region. As expected, terrain elevation is identified as a major factor influencing local ozone levels. Episodes of high ozone concentrations (≥90 ppb) in the park are shown to be primarily attributable to the transport of ozone into the park from outside. Backward air trajectories computed for high-ozone episodes in the GSMNP reveal that no preferred source regions exist, although some episodes appear to be associated with transport from urban areas.

Chemical deposition to a high elevation red spruce forest

A preliminary analysis of O3, SO2, SOinf4sup2−, and total NOinf3sup− deposition to the red spruce forest on the summit of Whitetop Mountain, Virginia, illustrates uncertainties in analysis methodologies, establishes the relative importance of three deposition pathways, and suggests areas for further research. Results are presented here for an analysis of the dry, wet (precipitation), and cloud water deposition pathways for the four chemical species during a 26-day period in April and May 1986. Dry and cloud water depositions are estimated using available models along with air and cloud water chemistry measurements made at the summit. For water soluble species, depositions by precipitation and cloud interception are found to be comparable in magnitude, while dry deposition appears to be about an order of magnitude less. High levels of atmospheric O3 lead to a large estimate of 03 deposition (on a mass flux basis) when compared to the estimated deposition of gaseous SO2. This is in spite of the fact that computed SO2 dry deposition velocities exceed those for O3. Model uncertainties are large for both dry deposition velocity and cloud water flux computations, and some bias in computations probably exists because of the application of the models to a complex terrain situation. Field evaluation of the cloud water deposition model is of greatest priority because of the apparent relative importance of that deposition pathway.

An Optimal Model Output Calibration Algorithm Suitable for Objective Temperature Forecasting

Abstract An optimal model output calibration (MOC) algorithm suitable for surface air temperature forecasts is proposed and tested with the National Centers for Environmental Prediction Regional Spectral Model (RSM). Differing from existing methodologies and the traditional model output statistics (MOS) technique, the MOC algorithm uses forecasts and observations of the most recent 2–4 weeks to objectively estimate and adjust the current model forecast errors and make refined predictions. The MOC equation, a multivariate linear regression equation with forecast error being the predictand, objectively screens as many as 30 candidates of predictors and optimally selects no more than 6. The equation varies from day to day and from site to site. Since it does not rely on long-term statistics of stable model runs, the MOC minimizes the influence of changes in model physics and spatial resolution on the forecast refinement process. Forecast experiments were conducted for six major urban centers in the Tennessee...

Estimating cloud water deposition to subalpine spruce-fir forests—I. Modifications to an existing model

Abstract A previously published steady-state model for computing cloud water deposition to a subalpine balsam fir ( Abies balsamea ) forest was modified for more generalized application to spruce-fir forests. One modification provided options for describing the cloud droplet size spectrum using observed relationships, in the vicinity of high elevation forests, between cloud liquid water content and the distribution of droplet size. Another modification implemented an optional experimental droplet collection efficiency parameterization scheme. This scheme computes collection efficiency for the most dense portion of a tree by treating it as a bulk collector rather than a multi-component (stems, branches, etc.) structure for which collection efficiency is determined by the individual collection efficiencies of its components. A study of model sensitivity to various physical parameterizations revealed that computations of gross cloud water flux to a canopy are most sensitive to canopy inhomogeneity, the relationship between cloud liquid water content and droplet size spectrum, and droplet collection efficiency. As expected, sensitivity test results also indicated that computed evaporation (and hence, the computed net cloud water flux) of intercepted cloud water from a canopy is strongly dependent on net radiation. The model modifications and sensitivity studies described here are the prelude to a test of the model described in a companion paper.

Estimating cloud water deposition to subalpine spruce-fir forests—II. Model testing

A modified version of a previously published steady-state model for computing cloud water deposition to a subalpine balsam fir (Abies balsamea) forest was tested using water throughfall data collected in a red spruce (Picea rubens) forest on Whitetop Mountain, Virginia. Detailed wind data were collected in two distinctly different spruce stands to define airflow conditions within the forest canopy. Other meteorological and canopy structure data were also collected for use as inputs to the deposition model. Model simulations of cloud deposition during 11 cloud events in the two forest stands revealed that the model performed best when site-specific wind speed profiles and droplet size spectra were used along with an experimental droplet collection efficiency scheme that treats the densest portions of trees as bulk collectors (as opposed to modelling collection efficiency for individual tree components). An analysis of residuals indicated that model errors were most strongly correlated with cloud liquid water content (W), a model input. It is speculated that the correlation with W was due to a combination measurement bias when clouds were thin or intermittent and a model computational bias when the potential (defined by the model) for the vertical turbulent flux of cloud water was high. Overall, computed values (using the optimally-configured model) of net cloud water flux tended to exceed measured throughfall rates by 20–30%, and the model explained 38–68% of the variance in throughfall rate. A comparison between the mechanistic model and a simpler empirical model indicated that the mechanistic model performed no better than its empirical counterpart.

Comparisons of Tetroon and Computed Trajectories

Abstract Forty-five tetroon flights made during the summer of 1980 for the PEPE/NEROS regions pollution studies, sponsored by the U.S. Environmental Protection Agency, were compared to computed trajectories based on National Weather Service rawinsonde wind fields. Most tetroon data were obtained for travel times of less than 10 h and travel distances of less than 150 km. Two trajectory computation algorithms were used. No significant differences were found between the two comparisons. Results of the comparisons indicate that the median measure of direction difference—the angle, determined in a clockwise sense, between tetroon and computed forward trajectory position vectors—has a bias of 11°. The average standard deviation of the direction difference is ±28°. About 10% of the total direction difference variance could be due to random tetroon motion; the remaining 90% is probably the result of error in the trajectory algorithms and/or the input data. Other significant results of the trajectory comparisons ...

Quantitative Precipitation Forecasting for the Tennessee and Cumberland River Watersheds Using the NCEP Regional Spectral Model

Abstract A limited-area spectral model—the Regional Spectral Model—developed at the National Centers for Environmental Prediction is used to prepare daily quantitative precipitation forecasts out to 48 h for the Tennessee and Cumberland River basins in the southeastern United States. One year of these forecasts is evaluated against data from a network of 243 rain gauges and against traditional man–machine forecasts provided under contract to Tennessee Valley Authority river system managers. The intent of this study was to determine whether the model forecasts, made at greater spatial resolution than those typically available from other sources, offered any advantages to water resource managers responsible for making critical day-to-day decisions affecting flood control, navigation, and hydropower production. The model’s performance, determined using a variety of statistical measures, was found to be more accurate than the traditional forecasts. In particular, the model had less bias and lower root-mean-sq...

Seasonal Aerosol Sulfate Trends for Selected Regions of the United States

Abstract Site and regional trends in seasonally averaged particle SO4 2− concentrations were examined for a large portion of the United States using data collected by the CASTNet air monitoring network. Trends were analyzed for overlapping periods of 1988–1999 and 1992–1999. The largest absolute SO4 2− decreases—approximately −0.4 μg/m3/yr—between 1988 and 1999 occurred in summer for sites in the Ohio River Valley and areas to the east. Generally, the largest SO4 2−, reductions were found for summer, but larger relative reductions often occurred for spring and autumn. Sulfate changes during 1992–1999 were quite different from those found for 1988–1999 and were not entirely consistent with changes in SO2 emissions. In some locations, the 1992–1999 period saw smaller declines in SO4 2−, while in other places seasonal SO4 2−, actually increased. Increases were mostly confined to summer and autumn across the southern and southwestern states. Multivariate analysis of ambient sulfur levels, by region, versus SO2 emissions reveals that annual emissions are associated with more than 80% of the variance in seasonal sulfur (SO2 and SO4 2−), in more than three-quarters of the cases examined. The weakest associations were found for the southeastern United States.