scholarly journals Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)

2014 ◽  
Vol 7 (6) ◽  
pp. 7619-7649
Author(s):  
B. H. Czader ◽  
P. Percell ◽  
D. Byun ◽  
Y. Choi
Keyword(s):  
Boundary Conditions ◽  
Initial Conditions ◽  
Meteorological Condition ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Detailed Chemistry ◽  
Mixing Ratios ◽  
Ozone Prediction ◽  
The Mean ◽  
Simulation Results

Abstract. A hybrid Lagrangian–Eulerian modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these file are available, this tool can run independently from the CMAQ whole domain simulation and it is designed to simulate source – receptor relationship upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias varies between −0.03 and −0.78 and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological condition, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of Lagrangian approach of using mean wind for its movement, but are still close, with the mean varying between 0.07 and −4.29 and slope varying between 0.95 and 1.063 for different analyzed cases. For historical reasons this hybrid Lagrangian – Eulerian tool is named the Screening Trajectory Ozone Prediction System (STOPS) but its use is not limited to ozone prediction as similarly to CMAQ it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.

scholarly journals Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)

2015 ◽  
Vol 8 (5) ◽  
pp. 1383-1394 ◽  
Author(s):  
B. H. Czader ◽  
P. Percell ◽  
D. Byun ◽  
S. Kim ◽  
Y. Choi
Keyword(s):  
Boundary Conditions ◽  
Initial Conditions ◽  
Surface Ozone ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Detailed Chemistry ◽  
Mixing Ratios ◽  
Ozone Prediction ◽  
The Mean ◽  
Simulation Results

Abstract. A hybrid Lagrangian–Eulerian based modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these files are available, this tool can run independently of the CMAQ whole domain simulation, and it is designed to simulate source–receptor relationships upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period, with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias for surface ozone mixing ratios varies between −0.03 and −0.78 ppbV and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological conditions, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of the Lagrangian approach of using mean wind for its movement, but are still close, with the mean bias for ozone varying between 0.07 and −4.29 ppbV and the slope varying between 0.95 and 1.06 for different analyzed cases. For historical reasons, this hybrid Lagrangian–Eulerian based tool is named the Screening Trajectory Ozone Prediction System (STOPS), but its use is not limited to ozone prediction as, similarly to CMAQ, it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.

scholarly journals Development of Korean Air Quality Prediction System version 1 (KAQPS v1) with focuses on practical issues

2020 ◽  
Vol 13 (3) ◽  
pp. 1055-1073 ◽  
Author(s):  
Kyunghwa Lee ◽  
Jinhyeok Yu ◽  
Sojin Lee ◽  
Mieun Park ◽  
Hun Hong ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Air Quality ◽  
Initial Conditions ◽  
Optimal Interpolation ◽  
Quality Prediction ◽  
Prediction System ◽  
Monitoring Networks ◽  
Alkyl Nitrates ◽  
Mixing Ratios ◽  
Air Quality Prediction

Abstract. For the purpose of providing reliable and robust air quality predictions, an air quality prediction system was developed for the main air quality criteria species in South Korea (PM10, PM2.5, CO, O3 and SO2). The main caveat of the system is to prepare the initial conditions (ICs) of the Community Multiscale Air Quality (CMAQ) model simulations using observations from the Geostationary Ocean Color Imager (GOCI) and ground-based monitoring networks in northeast Asia. The performance of the air quality prediction system was evaluated during the Korea-United States Air Quality Study (KORUS-AQ) campaign period (1 May–12 June 2016). Data assimilation (DA) of optimal interpolation (OI) with Kalman filter was used in this study. One major advantage of the system is that it can predict not only particulate matter (PM) concentrations but also PM chemical composition including five main constituents: sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), organic aerosols (OAs) and elemental carbon (EC). In addition, it is also capable of predicting the concentrations of gaseous pollutants (CO, O3 and SO2). In this sense, this new air quality prediction system is comprehensive. The results with the ICs (DA RUN) were compared with those of the CMAQ simulations without ICs (BASE RUN). For almost all of the species, the application of ICs led to improved performance in terms of correlation, errors and biases over the entire campaign period. The DA RUN agreed reasonably well with the observations for PM10 (index of agreement IOA =0.60; mean bias MB =-13.54) and PM2.5 (IOA =0.71; MB =-2.43) as compared to the BASE RUN for PM10 (IOA =0.51; MB =-27.18) and PM2.5 (IOA =0.67; MB =-9.9). A significant improvement was also found with the DA RUN in terms of bias. For example, for CO, the MB of −0.27 (BASE RUN) was greatly enhanced to −0.036 (DA RUN). In the cases of O3 and SO2, the DA RUN also showed better performance than the BASE RUN. Further, several more practical issues frequently encountered in the air quality prediction system were also discussed. In order to attain more accurate ozone predictions, the DA of NO2 mixing ratios should be implemented with careful consideration of the measurement artifacts (i.e., inclusion of alkyl nitrates, HNO3 and peroxyacetyl nitrates – PANs – in the ground-observed NO2 mixing ratios). It was also discussed that, in order to ensure accurate nocturnal predictions of the concentrations of the ambient species, accurate predictions of the mixing layer heights (MLHs) should be achieved from the meteorological modeling. Several advantages of the current air quality prediction system, such as its non-static free-parameter scheme, dust episode prediction and possible multiple implementations of DA prior to actual predictions, were also discussed. These configurations are all possible because the current DA system is not computationally expensive. In the ongoing and future works, more advanced DA techniques such as the 3D variational (3DVAR) method and ensemble Kalman filter (EnK) are being tested and will be introduced to the Korean air quality prediction system (KAQPS).

scholarly journals Development of Korean Air Quality Prediction System version 1 (KAQPS v1): an operational air quality prediction system with focuses on practical issues

2019 ◽  
Author(s):  
Kyunghwa Lee ◽  
Jinhyeok Yu ◽  
Sojin Lee ◽  
Mieun Park ◽  
Hun Hong ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Air Quality ◽  
Initial Conditions ◽  
Optimal Interpolation ◽  
Quality Prediction ◽  
Prediction System ◽  
Monitoring Networks ◽  
Alkyl Nitrates ◽  
Mixing Ratios ◽  
Air Quality Prediction

Abstract. For the purpose of providing reliable and robust air quality predictions, an operational air quality prediction system was developed for the main air quality criteria species in South Korea (PM10, PM2.5, CO, O3, and SO2). The main caveat of the system is to prepare the initial conditions (ICs) of the Community Multi-scale Air Quality (CMAQ) model simulations using observations from the Geostationary Ocean Color Imager (GOCI) and ground-based monitoring networks in northeast Asia. The performance of the air quality prediction system was evaluated during the Korea-United States Air Quality Study (KORUS-AQ) campaign period (1 May–12 June 2016). Data assimilation (DA) of optimal interpolation (OI) with Kalman filter was used in this study. One major advantage of the system is that it can predict not only particulate matter (PM) concentrations but also PM chemical composition including five main constituents: sulfate, nitrate, ammonium, organic aerosols (OAs), and elemental carbon (EC). In addition, it is also capable of predicting the concentrations of gaseous pollutants (CO, O3 and SO2). In this sense, this new operational air quality prediction system is comprehensive. The results with the ICs (DA RUN) were compared with those of the CMAQ simulations without ICs (BASE RUN). For almost all of the species, the application of ICs led to improved performance in terms of correlation, errors, and biases over the entire campaign period. The DA RUN agreed reasonably well with the observations for PM10 (IOA = 0.60; MB = −13.54) and PM2.5 (IOA = 0.71; MB = −2.43) as compared to the BASE RUN for PM10 (IOA = 0.51; MB = −27.18) and PM2.5 (IOA = 0.67; MB = −9.9). A significant improvement was also found with the DA RUN in terms of bias. For example, for CO, the MB of −0.27 (BASE RUN) was greatly enhanced to −0.036 (DA RUN). In the cases of O3 and SO2, the DA RUN also showed better performance than the BASE RUN. Further, several more practical issues frequently encountered in the operational air quality prediction system were also discussed. In order to attain more accurate ozone predictions, the DA of NO2 mixing ratios should be implemented with careful consideration of the measurement artifacts (i.e., inclusion of alkyl nitrates, HNO3, and PANs in the ground-observed NO2 mixing ratios). It was also discussed that, in order to ensure accurate nocturnal predictions of the concentrations of the ambient species, accurate predictions of the mixing layer heights (MLH) should be achieved from the meteorological modeling. Several advantages of the current air quality prediction system, such as its non-static free parameter scheme, dust episode prediction, and possible multiple implementations of DA prior to actual predictions, were also discussed. These configurations are all possible because the current DA system is not computationally expensive. In the ongoing and future works, more advanced DA techniques such as the three-dimensional variational (3DVAR) method and ensemble Kalman filter (EnK) are being tested and will be introduced to the Korean operational air quality forecasting system.

Suppression of String Vibration Using a Constraint Actuator at One Boundary

2010 ◽  
Author(s):  
Assaad AlSahlani ◽  
Ranjan Mukherjee
Keyword(s):  
Initial Conditions ◽  
Energy Content ◽  
Small Distance ◽  
Travel Distance ◽  
Physical Interaction ◽  
Time Of Application ◽  
String Vibration ◽  
Vibrating String ◽  
The Mean ◽  
Simulation Results

The problem of a vibrating string subjected to a sudden constraint at one boundary is investigated in this paper. The constraint is imposed by a sleeve that axially moves along the mean position of the string with a small distance. The constraint is applied instantaneously such that the geometry of the string outside the sleeve, immediately after application of the constraint, remains unchanged whereas the length of string covered by the sleeve remains at rest. The change in energy of the string after application and removal of the sleeve is investigated for different values of sleeve travel distance and time of application of the constraint. Analytical and numerical simulation results are first provided for the string vibrating in the first mode, and then for a more general case where the string has arbitrary initial conditions. The results show that the energy content can decrease or increase depending on the time of application of the constraint and sleeve travel distance. This provides the opportunity for active control of string vibration through direct physical interaction with a small portion of the string by using the sleeve as an actuator.

scholarly journals Verification of a short-range ensemble precipitation prediction system over Iberia

2010 ◽  
Vol 25 ◽  
pp. 55-63 ◽  
Author(s):  
D. Santos-Muñoz ◽  
M. L. Martin ◽  
A. Morata ◽  
F. Valero ◽  
A. Pascual
Keyword(s):  
Short Range ◽  
Initial Conditions ◽  
Ensemble Prediction ◽  
Positive Contribution ◽  
Prediction System ◽  
Good Reliability ◽  
Ensemble Prediction System ◽  
Probabilistic Forecasts ◽  
Ensemble Mean ◽  
The Mean

Abstract. The purpose of this paper is the verification of a short-range ensemble prediction system (SREPS) built with five different model physical process parameterization schemes and two different initial conditions from global models, allowing to construct several versions of the non-hydrostatic mesoscale MM5 model for a 1-month period of October 2006. From the SREPS, flow-dependent probabilistic forecasts are provided by means of predictive probability distributions over the Iberian Peninsula down to 10-km grid spacing. In order to carry out the verification, 25 km grid of observational precipitation records over Spain from the Spanish Climatic Network has been used to evaluate the ensemble accuracy together with the mean model performance and forecast variability by means of comparisons between such records and the ensemble forecasts. This verification has been carried out upscaling the 10 km probabilistic forecast to the observational data grid. Temporal evolution of precipitation forecasts for spatial averaged ensemble members and the ensemble mean is shown, illustrating the consistency of the SREPS. Such evolutions summarize the SREPS information, showing each of the members as well as the ensemble mean evolutions. The Talagrand diagram derived from the SREPS results shows underdispersion which indicates some bias behaviour. The Relative Operating Characteristic (ROC) curve shows a very outstanding area, indicating potential usefulness of the forecasting system. The forecast probability and the mean observed frequency present good agreement with the SREPS results close to the no-skill line. Because the probability has a good reliability and a positive contribution to the brier skill score, a positive value of this skill is obtained. Moreover, the probabilistic meteogram of the spatial daily mean precipitation values shows the range of forecast values, providing discrete probability information in different quantile intervals. The epsgram shows different daily distributions, indicating the predictability of each day.

Dynamics of the macromolecular composition of the biomass of microalgae in the morning under natural light. Model

2020 ◽  
pp. 45-52
Author(s):  
Alexander S. Lelekov ◽  
Anton V. Shiryaev
Keyword(s):  
Biochemical Composition ◽  
Initial Conditions ◽  
Natural Light ◽  
Photoautotrophic Growth ◽  
Structural Part ◽  
Basic Model ◽  
Microalgae Culture ◽  
Simulation Results ◽  
Structural Parts ◽  
Macromolecular Composition

The work is devoted to modeling the growth of optically dense microalgae cultures in natural light. The basic model is based on the idea of the two-stage photoautotrophic growth of microalgae. It is shown that the increase in the intensity of sunlight in the first half of the day can be described by a linear equation. Analytical equations for the growth of biomass of microalgae and its macromolecular components are obtained. As the initial conditions, it is assumed that at the time of sunrise, the concentration of reserve biomass compounds is zero. The simulation results show that after sunrise, the growth of the microalgae culture is due only to an increase in the reserve part of the biomass, while the structural part practically does not change over six hours. Changes in the ratio of the reserve and structural parts of the biomass indicate a change in the biochemical composition of cells.

DYNAMICS OF THERMAL LOSSES BY CONVECTION AND RADIATION OF THE SPHERICAL HEAT ACCUMULATOR OF SOLAR PLANTS

2020 ◽  
Vol 4 (41) ◽  
pp. 57-62
Author(s):  
SHAVKAT KLYCHEV ◽  
◽  
BAKHRAMOV SAGDULLA ◽  
VALERIY KHARCHENKO ◽  
VLADIMIR PANCHENKO ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Heat Loss ◽  
Initial Conditions ◽  
Water System ◽  
Heat Losses ◽  
Research Purpose ◽  
Heat Accumulator ◽  
Water Heaters ◽  
Intrinsic Radiation ◽  
Over Time

There are needed energy (heat) accumulators to increase the efficiency of solar installations, including solar collectors (water heaters, air heaters, dryers). One of the tasks of designing heat accumulators is to ensure its minimal heat loss. The article considers the problem of determining the distribution of temperatures and heat losses by convection and radiation of the heat insulation-accumulating body (water) system for a ball heat accumulator under symmetric boundary conditions. The problem is solved numerically according to the program developed on the basis of the proposed «gap method». (Research purpose) The research purpose is in determining heat losses by convection and radiation of a two-layer ball heat accumulator with symmetric boundary conditions. (Materials and methods) Authors used the Fourier heat equation for spherical bodies. The article presents the determined boundary and initial conditions for bodies and their surfaces. (Results and discussion) The thickness of the insulation and the volume of the heat accumulator affect the dynamics and values of heat loss. The effect of increasing the thickness of the thermal insulation decreases with increasing its thickness, starting with a certain volume of the heat accumulator or with R > 0.3 meters, the heat losses change almost linearly over time. The dynamics of heat loss decreases with increasing shelf life, but the losses remain large. (Conclusions) Authors have developed a method and program for numerical calculation of heat loss and temperature over time in a spherical two-layer heat accumulator with symmetric boundary conditions, taking into account both falling and intrinsic radiation. The proposed method allows to unify the boundary conditions between contacting bodies.

scholarly journals Behavior Modeling for a Beacon-Based Indoor Location System

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4839
Author(s):  
Aritz Bilbao-Jayo ◽  
Aitor Almeida ◽  
Ilaria Sergi ◽  
Teodoro Montanaro ◽  
Luca Fasano ◽  
...  
Keyword(s):  
Behavior Modeling ◽  
Percentage Error ◽  
Location Prediction ◽  
Indoor Environments ◽  
Prediction System ◽  
Indoor Location ◽  
The Mean ◽  
Locating System ◽  
Monitoring Devices ◽  
Do So

In this work we performed a comparison between two different approaches to track a person in indoor environments using a locating system based on BLE technology with a smartphone and a smartwatch as monitoring devices. To do so, we provide the system architecture we designed and describe how the different elements of the proposed system interact with each other. Moreover, we have evaluated the system’s performance by computing the mean percentage error in the detection of the indoor position. Finally, we present a novel location prediction system based on neural embeddings, and a soft-attention mechanism, which is able to predict user’s next location with 67% accuracy.

scholarly journals Simulations of Switchback, Fragmentation and Sunspot Pair in δ-Sunspots during Magnetic Flux Emergence

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 586
Author(s):  
Che-Jui Chang ◽  
Jean-Fu Kiang
Keyword(s):  
Magnetic Field ◽  
Solar System ◽  
Field Strength ◽  
Magnetic Flux ◽  
Initial Conditions ◽  
Observation Data ◽  
Flux Emergence ◽  
Polarity Inversion ◽  
Simulation Results ◽  
Spot Type

Strong flares and coronal mass ejections (CMEs), launched from δ-sunspots, are the most catastrophic energy-releasing events in the solar system. The formations of δ-sunspots and relevant polarity inversion lines (PILs) are crucial for the understanding of flare eruptions and CMEs. In this work, the kink-stable, spot-spot-type δ-sunspots induced by flux emergence are simulated, under different subphotospheric initial conditions of magnetic field strength, radius, twist, and depth. The time evolution of various plasma variables of the δ-sunspots are simulated and compared with the observation data, including magnetic bipolar structures, relevant PILs, and temperature. The simulation results show that magnetic polarities display switchbacks at a certain stage and then split into numerous fragments. The simulated fragmentation phenomenon in some δ-sunspots may provide leads for future observations in the field.

scholarly journals Solving nonlinear third-order three-point boundary value problems by boundary shape functions methods

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Ji Lin ◽  
Yuhui Zhang ◽  
Chein-Shan Liu
Keyword(s):  
Boundary Conditions ◽  
Boundary Value Problems ◽  
Initial Conditions ◽  
Boundary Value ◽  
Accurate Solution ◽  
Point Boundary ◽  
Third Order ◽  
Boundary Shape ◽  
Free Function ◽  
New Algorithms

AbstractFor nonlinear third-order three-point boundary value problems (BVPs), we develop two algorithms to find solutions, which automatically satisfy the specified three-point boundary conditions. We construct a boundary shape function (BSF), which is designed to automatically satisfy the boundary conditions and can be employed to develop new algorithms by assigning two different roles of free function in the BSF. In the first algorithm, we let the free functions be complete functions and the BSFs be the new bases of the solution, which not only satisfy the boundary conditions automatically, but also can be used to find solution by a collocation technique. In the second algorithm, we let the BSF be the solution of the BVP and the free function be another new variable, such that we can transform the BVP to a corresponding initial value problem for the new variable, whose initial conditions are given arbitrarily and terminal values are determined by iterations; hence, we can quickly find very accurate solution of nonlinear third-order three-point BVP through a few iterations. Numerical examples confirm the performance of the new algorithms.

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