Search

Recent research in several fields such as Biotechnology and Healthcare has uncovered a vast number of applications where 3D Electron Microscopy (EM) is useful. However, images produced by 3D EM are in most cases severely degraded. These degradations arise due to a multitude of reasons, e.g. the complex electronics in the system, magnetic lens aberration, heating and motion stability, charging, etc. Although the raw, degraded images are currently used for analysis, their usefulness is limited because the degradations make visual distinction and automated analysis of biological features very difficult. In this work, we give an analysis of noise, as one of the most important degradations in 3D EM imaging. Next, we propose a Non-Local Means image restoration algorithm that exploits the derived noise characteristics. The proposed algorithm yields significant improvements compared to other state-of-the-art image restoration algorithms.

The authors have performed a numerical experiment using Mesoscale Model 5 (MM5) with a horizontal resolution of 9 km to simulate hourly atmospheric dynamics and thermodynamics along the U.S. California coast for all of June 1996. The MM5 results were evaluated using more than 18 000 data points from wind profilers, radiosondes, buoys, and land stations; the results support the use of modeled dynamics for reliable monthly statistics and calculation of diurnal variations. Month-long mesoscale simulations of the marine atmospheric boundary layer (MABL) and satellite observations have been used to investigate the diurnal variation of near-shore and farther offshore clouds along the U.S. California coast. The authors extended the usual model evaluation with respect to time series and power spectrum analysis to investigate a link between the evaluated dynamics and satellite-derived cloudiness. Two distinct types of cloudiness variation were revealed. One is in the near-shore zone, extending approximate...

A case of fog formation along the California coast is examined with the aid of a one-dimensional, higherorder, turbulence-closure model in conjunction with a set of myriad observations. The event is characterized by persistent along-coast winds in the marine layer, and this pattern justifies a Lagrangian approach to the study. A slab of marine layer air is tracked from the waters near the California‐Oregon border to the California bight over a 2-day period. Observations indicate that the marine layer is covered by stratus cloud and comes under the influence of large-scale subsidence and progressively increasing sea surface temperature along the southbound trajectory. It is hypothesized that cloud-top cooling and large-scale subsidence are paramount to the fog formation process. The one-dimensional model, evaluated with various observations along the Lagrangian path, is used to test the hypothesis. The principal findings of the study are 1) fog forms in response to relatively long preconditioning of the marine layer, 2) radiative cooling at the cloud top is the primary mechanism for cooling and mixing the cloud-topped marine layer, and 3) subsidence acts to strengthen the inversion above the cloud top and forces lowering of the cloud. Although the positive fluxes of sensible and latent heat at the air‐sea interface are the factors that govern the onset of fog, sensitivity studies with the one-dimensional model indicate that these sensible and latent heat fluxes are of secondary importance as compared to subsidence and cloud-top cooling. Sensitivity tests also suggest that there is an optimal inversion strength favorable to fog formation and that the moisture conditions above the inversion influence fog evolution.

The recorded exceedances of the 24-hr PM10 National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM10 impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM10 impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.

The authors have developed a method that uses tracer measurements as the basis for comparing and evaluating wind fields. An important advantage of the method is that the wind fields are evaluated from the tracer measurements without introducing dispersion calculations. The method can be applied to wind fields predicted by different atmospheric models or to wind fields obtained from interpolation and extrapolation of measured data. The method uses a cost function to quantify the success of wind fields in representing tracer transport. A cost function, “tracer potential,” is defined to account for the magnitude of the tracer concentration at the tracer receptors and the separation between each segment of a trajectory representing wind field transport and each of the tracer receptors. The tracer potential resembles a general expression for a physical potential because the success of a wind field trajectory is directly proportional to the magnitude of the tracer concentration and inversely proportion...

A fully compressible cloud-resolving model was developed based on the MacCormack numerical scheme with a shortwave radiation scheme based on the Monte Carlo method. On the basis of the results from a numerical experiment with a buoyant bubble in the neutral atmosphere, the model exhibited close correlation with other similar compressible models. The radiation scheme was evaluated using the data reported by Nicholls [Nicholls, S., 1984. The dynamics of stratocumulus: aircraft observations and comparison with a mixed layer model. Q. J. R. Meteorol. Soc. 110, 783–820.]. Use of the model permitted accurate reproduction of the structure of measured shortwave radiation fluxes. Various accuracy and sensitivity tests were conducted. It was found that more than 10,000 photons were needed to provide sufficient accuracy. The present Monte Carlo radiation scheme appeared to be computationally more efficient than the Streamer model with the eight streams option. The sensitivity tests indicated that the optical thickness was the most critical parameter in the calculations of shortwave radiative fluxes. A comparison of radiation flux fields for broken- and solid-cloud cases showed significant differences confirming that the Monte Carlo method is the most appropriate for flux calculations in a broken-cloud case.

Our atmosphere is a great natural laboratory. Atmospheric scientists can use this laboratory to look for physical phenomena, to teach physical ideas and to develop practical technologies.

Spatial and temporal characteristics of the wind velocity in complex terrain, relevant to wind energy resources were investigated in this study. Data from one 80 m and four 50 m towers located within a range of 200 km in western Nevada, U.S., operated from August 2003 to March 2008 were used in the analysis. The average multi-annual wind speed did not show significant increase trends with increased elevation, the differences are mainly governed by the complexity of the topography including local circulations and channeling. Due to a slower increase of the standard deviation of the wind speed compared to the increase of the average wind speed, the turbulence intensity slowly decreased with an increase of the average wind speed. The wind speed was modeled using the Weibull distribution, while the wind direction was modeled using the von Mises distribution. In spite of differences in the basic wind speed statistics, the auto- and cross-correlations show a strong coherence between the wind speed and direction with slowly decreasing amplitude of the multi-day periodicity with increasing lag periods. A non-zero centerline of the diurnal component in the autocorrelation function indicated a possible long-term periodicity. Besides a pronounced diurnal periodicity at all locations, the spectral analysis showed significant annual periodicity with similar characteristics at all five locations.

Physical and chemical characteristics within the two distinct meteorological regimes, i.e., convective and stable atmospheric conditions in a complex highly urbanized terrain of the California South Coast Air Basin (CSCAB; the Los Angeles area) were investigated. The Community Multi-scale Air Quality (CMAQ) model was used with a horizontal resolution of 5 km × 5 km to produce the 3D fields of pollutant concentrations. Input meteorological fields were obtained by the MM5 numerical weather prediction model while the input emissions were provided by the Californian Environmental Protection Agency. Modeled meteorological surface parameters and their vertical profiles as well as modeled planetary boundary layer heights (PBL) were compared to the corresponding measurements. The CMAQ simulations of ozone concentrations were compared against the relatively large number of measurements from the CSCAB area. The main goal of the research was to identify the governing atmospheric processes and sources in the coastal area that contributed to the high levels of pollution and to investigate the air quality model’s capabilities to simulate the air quality in the complex topography.

The overall objective of this study was to improve the representation of regional ocean circulation in the North Pacific by using high resolution atmospheric forcing that accurately represents mesoscale processes in ocean-atmosphere regional (North Pacific) model configuration. The goal was to assess the importance of accurate representation of mesoscale processes in the atmosphere and the ocean on large scale circulation. This is an important question, as mesoscale processes in the atmosphere which are resolved by the high resolution mesoscale atmospheric models such as Weather Research and Forecasting (WRF), are absent in commonly used atmospheric forcing such as CORE forcing, employed in e.g. the Community Climate System Model (CCSM).

A three-dimensional higher-order closure dispersion model is used to simulate dispersion from an elevated point source in an area with complex terrain in the Colorado River Valley (southwestern U.S ...

[1] Analysis of sea surface temperature (SST) from coastal buoys suggests that the summertime over-shelf water temperature off the U.S. West Coast has been declining during the past 30 years at an average rate of −0.19°C decade−1. This cooling trend manifests itself more strongly off south-central California than off Oregon and northern California. The variability and trend in the upwelling north of off San Francisco are positively correlated with those of the equatorward wind, indicating a role of offshore Ekman transport in the north. In contrast, Ekman pumping associated with wind stress curls better explains the stronger and statistically more significant cooling trend in the south. While the coast-wide variability and trend in SST are strongly correlated with those of large-scale modes of climate variability, they in general fail to explain the southward intensification of the trend in SST and wind stress curl. This result suggests that the local wind stress curl, often topographically forced, may have played a role in the upwelling trend pattern.

Wind turbine power performance for the energy production calculations has traditionally been modeled assuming a set of simple average input meteorological conditions. Wind turbine power curve tests are also performed with this assumption, based on criteria defined in the IEC-12-1 standard. While this approach has proven to be adequate for the wind industry for several years, the increasing size of wind turbines (WT)—coupled with an improved awareness of the wind flow variation throughout the boundary layer—has generated concern that the effects of complex meteorological conditions on turbine power performance are not well understood. However, the uncertainty of power performance measurements is closely related to the uncertainty in the wind velocity, turbulence and other meteorological parameters and their effects on the wind turbine performances.

Sub-kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50-m towers in west-central Nevada during July and December 2007. Moment-based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near-surface wind shear ; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root-mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub-diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy-containing motions. Neither of the verification metrics showed systematic improvement in the models' accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment-based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy-containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer- than-diurnal than for sub-diurnal periods. Finally, the study shows that at least near- kilometer horizontal grid spacing is necessary for dynamical downscaling of near-surface wind speed climate over complex terrain ; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy- containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows.

The characteristics of dynamics and thermodynamics of the atmospheric boundary layer in a part of the Colorado River Valley, centered around Lake Mohave, have been investigated by analysis of measurements conducted during a field program in late spring and early summer of 1986 and a series of numerical simulations by a three-dimensional second-moment turbulence-closure model. The model was validated against measurements described in a companion article (Enger et al., 1993). According to airsonde measurements performed on eight nights, the depth of the surface inversion was around 200 m with an average temperature gradient of about 30 K km −1 . Analysis of acoustic sounder data collected during one month revealed significant diurnal variations of U and V wind-speed components related to slope and valley flows, respectively

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55-0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30-0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases.

A higher order closure model is applied to simulate the dynamics in an area with a deep valley characterized by complex terrain in the southwestern US. The simulation results show generally good agreement with measured profiles at two locations within the valley. Both the measurements and the simulations indicate that the flow dynamics in the area are highly influenced by the topography and meandering of the valley, and can be resolved only by the full three-dimensional model code. The wind veering simulated over the range of the topographic elevations is often larger than 100 deg and in some cases as large as 180 deg, as a consequence of topographic forcing. In the case of an infinitely long valley, as is assumed in two-dimensional test simulations, a strong low-level jet occurs within the valley during stable conditions. The jet is mainly a consequence of the Coriolis effect. However, the jet development is significantly reduced due to asymmetric effects of the actual topography treated in the three-dimensional simulations. Tests with the two-dimensional nonhydrostatic version of the model show significant wave responses for a stable stratified flow over the valley. The structure resembles nonlinear mesoscale lee waves, which are intrinsically nonhydrostatic. However, considering the three-dimensional nature of this valley system, a better understanding and verification of the nonhydrostatic effects requires both a three-dimensional nonhydrostatic numerical model and an observational data set which is fully representative in all three dimensions.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM2.5 (particulate matter with aerodynamic diameter2.5 microm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to chi2 and R2 used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis. For the most part, factors are found to represent imperfect combinations of sources, and the optimal number of factors should be just adequate to explain the input data (e.g., R20.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.

The ability of receptor models to estimate regional contributions to fine particulate matter (PM2.5) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM2.5 chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM2.5 source profiles from the U.S. Environmental Protection Agency (EPA)'s SPECIATE and Desert Research Institute's source profile databases. CMAQ estimated the "true" contributions of seven regions in the eastern United States to chemical species concentrations and individual source contributions to primary PM2.5 at both sites. A seven-factor solution by the positive matrix factorization (PMF) receptor model explained approximately 99% of the variability in the data at both sites. At BRIG, PMF captured the first four major contributing sources (including a secondary sul-fate factor), although diesel and gasoline vehicle contributions were not separated. However, at GRSM, the resolved factors did not correspond well to major PM2.5 sources. There were no correlations between PMF factors and regional contributions to sulfate at either site. Unmix produced five- and seven-factor solutions, including a secondary sulfate factor, at both sites. Some PMF factors were combined or missing in the Unmix factors. The trajectory mass balance regression (TMBR) model apportioned sulfate concentrations to the seven source regions using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectories based on Meteorological Model Version 5 (MM5) and Eta Data Simulation System (EDAS) meteorological input. The largest estimated sulfate contributions at both sites were from the local regions; this agreed qualitatively with the true regional apportionments. Estimated regional contributions depended on the starting elevation of the trajectories and on the meteorological input data.

The effects of longwave and shortwave radiative heating on the coupling between stratocumulus clouds and the boundary layer is investigated using a one-dimensional second-moment turbulence-closure model. The decoupling of a stratiform cloud from the subcloud layer is often a precursor to cloud break up and the transition to scattered cumulus clouds or clear sky. Coupling between cloud and subcloud layers is found to be very sensitive to cloud depth and subcloud layer sensible and latent heat fluxes. In particular, a strong moisture flux can maintain weak coupling between the cloud and subcloud layers so that the lower part of the cloud layer may continue to develop despite the formation of a stable temperature gradient between the top of the subcloud layer and cloud base.The effect of shortwave heating on decoupling is threefold. First, shortwave heating directly offsets the net longwave cooling at cloud top by as much as 30% (in February at latitude 29°N), reducing or eliminating the overall coo...

The goals of this project are to increase our understanding of weather predictability and its advantages and limitations, and to develop methods to provide more accurate forecasts and nowcasts in complex terrain using multi-model ensemble modeling techniques and special observations including remotely sensed data. The main objectives of the study are: 1) to further develop, test, and continue twice daily operational forecasts using both the real time Weather and Research Forecasting (WRF Version 3.2) model (Skamarock et al. 2008) and Mesoscale Model 5 (MM5 Version 3.7.2) (Grell et al. 1994) with subkilometer horizontal resolution to support the NOWCAST system at the Fallon Naval Air Station (NAS); 2) To extend the real time forecasting system with a continuous 15-day forecast using WRF as a testbed; 3) To analyze multi-model ensemble forecasting capabilities and to provide basis for a real time multi-model ensembles using WRF, MM5, and the Coastal Oceanic and Atmospheric Modeling Prediction System (COAMPSTM, Version 3.1.1) (Hodur 1997); 4) To develop a framework that complements the ensemble forecasting to better understand the sources of error and uncertainty in dynamical forecasts relevant to nowcasting key parameters such as wind speed, cloud fields, and visibility over the Fallon NAS area; and 5) To test the forecasting methodology for critical conditions of a dust storm affecting the southwest U.S. including the Fallon area.

The circulation along the California Coast in June 1999 was influenced by strong upwelling-favourable winds. To study the ocean circulation and upwelling variability, the Princeton Ocean Model (POM) was setup for the California and Baja California coasts and it was forced with interactively computed wind stress and surface heat fluxes. Atmospheric fields used in the surface flux estimates during the POM runs were obtained from Mesoscale Model 5 (MM5) outputs, while the sea surface temperatures (SST) were prescribed by the ocean model. One-way coupled air–sea modelling was used in the process-oriented approach to asses the influence of the wind stress, wind stress curl, initial density gradients, and nesting procedure with global model for the predicted circulation and accompanied upwelling. Hourly SSTs measured at twelve buoys operated by the National Data Buoy Center (NDBC) were used to evaluate sensitivity modelling studies via root-mean-squared-errors (RMSE). Low-pass filtered currents measured at 15 stations along central and southern Californian coast were also used in the ocean model evaluation procedures. In order to resolve the particular roles and importance of the wind stress vs. wind stress curl in driving coastal upwelling, besides baseline experiment we performed a numerical experiment with curl-free wind forcing. Modelled surface currents obtained in the baseline experiment indicate southward and southwestward flow in the deep ocean areas and alternating equatorward and poleward current near the shore. Wind stress curl appeared to be crucial both for the current field structure and SST distribution. The inshore poleward current obtained in the baseline experiment and evidenced by direct measurements was replaced with an equatorward current in the curl-free experiment. Furthermore, a significant temperature drop occurred along the entire coast in the curl-free experiment, whereas in the baseline the areas of maximum upwelling were confined to the regions with the wind maxima. Climatological temperature profile integrated with the satellite SST appeared to be superior for initialization of the ocean model in comparison with Levitus climatology. Due to too high temperatures predicted by HYbrid Coordinate Ocean Model (HYCOM) along the West Coast, expected improvement of the baseline experiment was not achieved by nesting POM with the Pacific-scale HYCOM. Additionally, a selection of a drag coefficient parameterization appears to have a significant impact on the upwelling evolution.

The goals of this project are to increase our understanding of weather predictability and to develop capabilities to provide more accurate forecasts and nowcasts in complex terrain using ensemble modeling techniques and special observations including remote sensing.

[1] During the summertime bora episode of 22–25 June 1995, characterized by hazardous weather conditions with strong winds of over 20 m s−1, two satellite-tracked drifters were present in the Adriatic shelf area. One was on the open sea south of the Istrian Peninsula, while the other, which measured the surface current of 70 cm s−1, was tracked along the western coastal strip. An oceanographic model, forced by the outputs of mesoscale meteorological models and by river discharges, was applied to simulate drifter trajectories during the event. Process-oriented studies performed to determine governing forcings for the drifter movements in different areas of the Adriatic revealed that strong current along the western Adriatic coast resulted from a combined influence of the wind stress and the river discharges. The wind was responsible for the strong drifter movements, while the baroclinic current due to the coastal buoyancy fluxes prevented the drifter from moving close to the shore and from colliding with the coast. At the same time, drifter movements in the open sea resulted from the wind action solely. Differences in the alongshore and offshore vertical density profiles, primarily due to the river inflows, caused 3 times stronger currents in the coastal area as compared to the currents in the open sea. The proper formulation of the drag coefficient was crucial for the successful simulations of the drifter trajectories, as simulations with increased values of the drag coefficient reproduced well the effects of the sea surface roughness and atmospheric instability above the sea.

The effect of a stable internal boundary layer (IBL) on the cloud-capped marine boundary layer is investigated using a one-dimensional second-order closure model. A stable IBL forms if there is a reversal in the surface buoyancy flux when warm air flows over colder water. These conditions exist in the vicinity of Ocean fronts where sea surface temperature discontinuities of about 2°C in 5 km have been observed. There is a balance between the buoyant consumption and inertial production of kinetic energy so that the layer remains weakly turbulent and can deepen due to shear-driven mixing. The stability of the layer limits momentum exchange with the air above so that there is a significant reduction in the surface stress in the IBL and an acceleration of the flow aloft. There are important implications for cloud development in regions of large ocean temperature gradients because a stable IBL can limit the vertical transfer of moisture from the surface to the upper part of the boundary layer. In addi...

Dust emissions due to low-level flight of a helicopter are studied as part of the Integrated Desert Terrain Forecasting for Military Operations project. Atmospheric concentrations of PM10 were measured at different heights downwind of the helicopter flight path. Digital video images captured the entrainment and dispersion of the dust plume formed by the wake of the helicopter during each pass down the flight course. The video data are analyzed to relate the dust plume strength to degradation of local visibility. A strong relationship between color changes/standard deviations and plume strength is found. This relationship is used to develop an algorithm that can determine local visibility degradation due to local PM10 concentrations around a helicopter. This algorithm can be combined with concentration output data from an atmospheric dispersion model to simulate visibility in a helicopter simulator.

The main objectives of the study were to support wind energy assessment for all of Nevada by providing two annual cycles of high-resolution mesoscale modeling evaluated by data from surface stations and towers, estimating differences between these annual cycles and standard wind maps, and providing wind and wind power density statistics at elevations relevant to turbine operations. In addition to the 65 existing Remote Automated Weather Stations in Nevada, four 50-m-tall meteorological towers were deployed in western Nevada to capture long-term wind characteristics and provide database input to verify and improve modeling results. The modeling methodology using Mesoscale Model 5 (MM5) was developed to provide wind and wind power density estimates representing mesoscale effects that include actual synoptic forcing during the two annual cycles (horizontal resolution on the order of 2 and 3 km). The results from the two annual simulation cycles show similar wind statistics with an average difference of less than 100 W/m2. The available TrueWind results for the wind power density at 50 m show greater values of wind power density compared to both MM5-simulated annual cycles for most of the area. However, mainly in the Sierras and the mountainous regions of southern and eastern Nevada, the MM5 simulations indicate greater values for wind power density. The results of this study suggest that the synthesis of the data from a network of tower observations and high-resolution mesoscale modeling is a crucial tool for assessing the wind power density in Nevada and, more generally, other topographically developed areas.

Chemically speciated PM2.5 and particle-bound polycyclic aromatic hydrocarbon (PAH) measurements were made at three sites near urban Tong Liang, Chongqing, a Chinese inland city where coal combustion is used for electricity generation and residential purposes outside of the central city. Ambient sampling was based on 72-hr averages between 3/2/2002 and 2/26/2003. Elevated PM2.5 and PAH concentrations were observed at all three sites, with the highest concentrations found in winter and the lowest in summer. This reflects a coupling effect of source variability and meteorological conditions. The PM2.5 mass estimated from sulfate, nitrate, ammonium, organics, elemental carbon, crustal material, and salt corresponded with the annual average gravimetric mass within +/-10%. Carbonaceous aerosol was the dominant species, while positive correlations between organic carbon and trace elements (e.g., As, Se, Br, Pb, and Zn) were consistent with coal-burning and motor vehicle contributions. Ambient particle-bound PAHs of molecular weight 168-266 were enriched by 1.5 to 3.5 times during the coal-fired power plant operational period. However, further investigation is needed to determine the relative contribution from residential and utility coal combustion and vehicular activities.

Indirect or passive observations using satellite remote sensing in the visible, infrared and microwave spectra provide global coverage of the thermal states of the cloud tops or the ground surface. The commonly employed temperature profile matching techniques using satellite data and numerical weather prediction models are only relatively successful in estimating the cloud top height (CTH) for optically dense middle and high clouds (cloud tops at heights generally greater than two kilometers). Therefore, accurate predictions of low-level CTH present a formidable challenge to the forecasting and nowcasting community. In this study, we present an approach to estimating low-level CTH by combining the above-cloud information extracted from the satellite imagery and the below-cloud information obtained from weather station measurements. Assumed ranges of brightness temperature and CTH are used to process the cloudy pixels for visualization and classification purposes. Our study indicates that the CTH evaluated using satellite data confirms the presence of low-level clouds in the range 400-1000 m. Accurate estimates of the boundary layer CTH can provide better low-level cloud products (e.g., fog or clouds formed by fog lifting) for improved weather forecasting and applications in the research community.

Accurate prediction of the transport and dispersion of atmospheric pollutants and tracers in complex terrain represents a significant research challenge. The differences between simulations and measurements are caused by model simplifications and assumptions, uncertainty in measurements, and variability of natural processes that have a random component. The uncertainties in the model and measurements could be reduced to certain extent, while the natural variability cannot be fully accounted for. In this study, we present a method of estimating uncertainties in the simulated dispersion as a residual term in the equation for the fractional error.

[1] Widespread sea fog off the California coast occurred in conjunction with a transient weather disturbance in mid-April 1999. In this paper we examine the larger-scale influences that have bearing on the fog formation and its dissipation. Furthermore, this event is viewed in the context of the monthly changes of weather along the California coast. We compare and contrast the fog event with the precedent synoptic event that was fog-free in an effort to understand the sensitivity of fog formation to large-scale parameters. The principal results of the study are (1) the sea fog is characterized by long over-water trajectories in persistent northwesterly flow. The sea surface temperatures (SSTs) are greater than the air temperature along these trajectories and gradual lowering of the stratus in the presence of strong subsidence eventually produces fog. (2) The synoptic-scale subsidence associated with the anticyclone in these transient weather systems is a critically important factor in sea fog formation: a persistent, large-magnitude subsidence favors fog by decreasing the depth of the marine layer while increasing the strength of the inversion. (3) Trajectories obtained by back-tracking foggy and fog-free air in the fog event of mid-April 1999 make it clear that air with a path history over land is less likely to be associated with sea fog. In short, the demarcation between foggy and fog-free zones is related to the differences in path history. (4) The occurrence of sea fog depends on the frequency of the transient weather systems, where an extended period of air mass transformation favors fog formation.

The goal of this project is to increase our understanding of the modification of complex atmospheric dynamics, cloudiness, and fog due to the interaction of the air, sea, and land in a coastal region. This increased understanding will lead to improvements in parameterizations of turbulence, cloudiness, and fog. In general, it will improve the episodic and seasonal forecasting of coastal weather over a wide spectrum of spatial and temporal scales. Specific project objectives include: 1) investigating the physical processes that lead to the formation, evolution, and dissipation of offshore fog; and 2) investigating the diurnal variability of the dynamics and cloudiness of the marine atmospheric boundary layer off the California and Oregon coasts. The project is supported by the Office of Naval Research, Marine Meteorology and Atmospheric Effects.

A numerical modelling study of the response of the Adriatic shelf waters and the Po River plume to a bora wind event has been undertaken using the Princeton Ocean Model (POM). After a bora episode from 16 to 20 January 1987, Advanced Very High Resolution Radiometer (AVHRR) satellite image revealed a cold filament protruding from the Italian coastal area toward the open sea. To understand and numerically simulate the offshore spreading of cold water from the western coastal area, the effects of three external forcings have been examined: wind stress, heat flux and river discharge. Wind stress and surface heat flux, calculated by bulk method from the winds, air temperatures and humidities obtained by Mesoscale Model 5 (MM5) with space and time resolution of 9 km and 1 h, respectively, were used to force the oceanographic model. River discharge was introduced in the oceanographic model as a source term in the continuity equation. Moreover, it was assumed that river water had zero salinity and a 5°C lower temperature than the surrounding sea water, following some climatological estimations. The results of numerous numerical experiments revealed that the filament observed in the AVHRR satellite image was formed by the joint action of three external forcings mentioned, and that none of them could be neglected while considering the observed pattern. Although the bora is, due to its NE direction, downwelling favourable wind for the western Adriatic coast, its alongshore variability induces offshore spreading of cold and less saline Po-influenced water. The effects of air stability and wind wave field are important for the wind stress estimation. The role of the Po River is to reduce sea surface salinity and to prevent cold water from sinking; it is introduced in the oceanographic model mainly through the initial salinity field. The combined effects of the basin topography and surface heat flux create an extra amount of cold water in the western coastal strip, which is then advected by bora wind action toward the open sea. High horizontal resolution of the numerical experiments is important in resolving the alongshore variability of the bora wind field and to correctly simulate the narrow filament observed in the AVHRR image.

When dealing with dispersion modeling in topographically complex surroundings there are several aspects to be considered. Does the topography give rise to preferred flow patterns, sea and land breeze cycles, mountain and valley winds, canalizations, etc.? When developing operational models there is also the question of available computer capacity. The selection of measurement locations in complex terrain, frequency of sampling, and selection of synoptic situations always place limits on the completeness of information about local flows. Observational studies provide useful information about the structure of parameters such as wind speed and direction, temperature, and humidity. However, one of the most critical issues is the structure of turbulence, which varies greatly over space and time in complex terrain and requires a great number of routine measurements to characterize. Determination of the turbulent transfer is essential to understanding and predicting the dispersion of atmospheric pollutants. Mountain flows are generally nonlinear and fully three-dimensional phenomena, and analytical models are applicable only to simple cases. In the present project, comparison of different dispersion models - a semi-Gaussian trajectory model and a higher-order closure dispersion model - will be performed. The observed or numerically simulated, by different dynamic models, wind, temperature, and turbulence fields will be used as inputs to these dispersion models. When choosing a modeling system, or combination of dynamic model and dispersion model, it is important to take into consideration the purpose of the simulations. If it is important to get good agreement between measurements and simulations for short-term sampling periods, a more complex modeling system needs to be used than if one is only interested in monthly, seasonally, or yearly mean values.

During November 1994 an extensive atmospheric field program was conducted in the Reno basin (see Hallett et al. 1995 in these proceedings). The main objective of the program was to investigate atmospheric dynamics and stability for various weather conditions ranging from stagnant wind periods associated with significant temperature inversions to frontal passage conditions. A 3-D Regional Atmospheric Modeling System (RAMS, Pielke et al. 1992) has been applied to a case study of extremely strong wind conditions which occurred in the Reno Basin on November 9,1994. The main objectives of this numerical study of atmospheric processes in complex terrain are: (a) to evaluate the stateof-the-art numerical model in predicting atmospheric processes occurring during the frontal passage; (b) to compare predicted wind shear, turbulence and stability parameters with the data measured by wind profiler, Radio Acoustic Sounding System (RASS), and radiosonde.