• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.27-38
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• 2009

The multi-level profile system is designed to measure the vertical profile of $H_2O$ and $CO_2$ concentrations in the surface layer to estimate the storage effects within the plant canopy. It is suitable for long-term experiments and can be used also in advection studies for estimating the spatial variability and vertical gradients in concentration. It enables the user to calculate vertical fluxes of water vapor, $CO_2$ and other trace gases using the surface layer similarity theory and to infer their sources or sinks. The profile system described in this report includes the following components: sampling system, calibration and flow control system, closed path infrared gas analyzer(IRGA), vacuum pump and a datalogger. The sampling system draws air from 8 inlets into the IRGA in a sequence, so that for 80 seconds air from all levels is measured. The calibration system, controlled by the datalogger, compensates for any deviations in the calibration of the IRGA by using gas sources with known concentrations. The datalogger switches the corresponding valves, measures the linearized voltages from the IRGA, calculates the concentrations for each monitoring level, performs statistical analysis and stores the final data. All critical components are mounted in an environmental enclosure and can operate with little maintenance over long periods of time. This report, as a practical manual, is designed to provide helpful information for those who are interested in using profile system to measure evapotranspiration and net ecosystem exchanges in complex terrain.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.6
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• pp.279-285
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• 2017

In general, the power law and logarithmic profile are commonly used as flow vertical velocity profile model. However, since the parameters of profile vary with characteristics of coastal environment, it is necessary to estimate these values from measured data using regression analysis. In this paper, we estimated the power law exponent (n), friction velocity ($u^*$) and roughness length ($z_0$) of logarithmic profile by analyzing measured tidal current data that are averaged at a interval of 30 min. In the results of analysis, power law exponent (n) was estimated to be about 10.75 during flood and about 9.3 during ebb. Meanwhile, $u^*$ of logarithmic profile was estimated to be about 0.084 m/s, 0.105 m/s during flood and ebb, respectively. Also, $z_0$ was estimated to be 0.004 m and 0.006 m, respectively.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.575-587
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• 2020

Meteorological phenomena are observed by the Korea Meteorological Administration in a variety of ways (e.g., surface, upper-air, marine, ocean, and aviation). However, there are limits to the meteorological observation of the planetary boundary layer (PBL) that greatly affects human life. In particular, observations using a sonde or aircraft require significant observational costs in economic terms. Therefore, the goal of this study was to measure and analyze the meteorological factors of the vertical distribution of the see-land breeze among local meteorological phenomena using meteorological drones. To investigate the spatial distribution of the see-land breeze, a same integrated meteorological sensor was mounted on each drone at three different points (seaside, bottom of mountain, and mountainside), including the Boseong tall tower (BTT) at the Boseong Standard Weather Observatory (BSWO) in the Boseong region. Vertical profile observations for air temperature, relative humidity, wind direction, wind speed, and air pressure were conducted up to 400 m every 30 minutes from 1100 LST to 1800 LST on August 4, 2018. The spatial characteristics of meteorological phenomena for temperature, relative humidity, and atmospheric pressure were not shown at the four points. Strong winds (~8 m s-1) were observed from the midpoint (~100 m) at strong solar radiation hour, and in the afternoon the wind direction changed from the upper layer at the inland area to the west wind. It is expected that the analysis results of the lower atmospheric layer observed using the meteorological drone may help to improve the weather forecast more accurately.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1041-1048
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• 2023

Wind LiDAR and Wind Profiler are devices that produce continuous vertical distribution of wind vector in high-resolution data, and their use has recently been increasing. Although the observation and data processing methods of the two devices are similar, differences in wind detection accuracy may occur depending on weather and operation settings. introduce the characteristics of the two instruments and wind calculation methods, and apply the latest instrument verification standards to evaluate their accuracy by comparing them with the wind observed with a radiosonde. Accordingly, a new direction for performance verification following the introduction of equipment and additional necessary complements are presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.819-826
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• 2020

The UHF band wind profiler radars of the Korea Meteorological Administration (KMA), which produces the vertical profile of the wind, need to be calibrated for better performance. The capabilities of the radar in detecting even light precipitation were used for the calibration of which reference takes the hourly series of ground rainfall rate measured by a rain gauge at the radar site. This calibration must be renewed regularly according to the methodology implemented in this work since errors occur on the wind vectors in the clear sky without reflectivity calibration. Comparing the wind by wind profiler with that by radiosonde, the optimal radar constant contributed to the improvement of wind accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.3
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• pp.227-235
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• 2015

Using eddy covariance method, net ecosystem exchange (NEE) of $CO_2$ ($F_{CO_2}$), $H_2O$ (LE), and sensible heat (H) can be approximated as the sum of eddy flux ($F_c$) and storage flux term ($F_s$). Depending on strength and distribution of sink/source of scalars and magnitude of vertical turbulence mixing, the rates of changes in scalars are different with height. In order to calculate $F_s$ accurately, the differences should be considered using scalar profile measurement. However, most of flux sites for agricultural lands in Asia do not operate profile system and estimate $F_s$ using single-level scalars from eddy covariance system under the assumption that the rates of changes in scalars are constant regardless of the height. In this study, we measured $F_c$ and $F_s$ of $CO_2$, $H_2O$, and air temperature ($T_a$) using eddy covariance and profile system (i.e., the multi-level measurement system in scalars from eddy covariance measurement height to the land surface) at the Chengmicheon farmland site in Korea (CFK) in order to quantify the differences between $F_s$ calculated by single-level measurements ($F_s_{-single}$ i.e., $F_s$ from scalars measured by profile system only at eddy covariance system measurement height) and $F_s$ calculated by profile measurements and verify the errors of NEE caused by $F_s_{-single}$. The rate of change in $CO_2$, $H_2O$, and Ta were varied with height depending on the magnitudes and distribution of sink and source and the stability in the atmospheric boundary layer. Thus, $F_s_{-single}$ underestimated or overestimated $F_s$ (especially 21% underestimation in $F_s$ of $CO_2$ around sunrise and sunset (0430-0800 h and 1630-2000 h)). For $F_{CO_2}$, the errors in $F_s_{-single}$ generated 3% and 2% underestimation of $F_{CO_2}$ during nighttime (2030-0400 h) and around sunrise and sunset, respectively. In the process of nighttime correction and partitioning of $F_{CO_2}$, these differences would cause an underestimation in carbon balance at the rice paddy. In contrast, there were little differences at the errors in LE and H caused by the error in $F_s_{-single}$, irrespective of time.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.841-848
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• 2020

The 1.29 GHz wind profiler radar is a remote observation device that is useful not only for calculating wind vectors in clear air, but also for detecting rainfall. The Doppler spectrum symmetry test is essential in the horizontal wind treatment process. Since asymmetry may be detected in rainfall cases, it is necessary to reflect in the wind calculation algorithm that the sign of the radial velocity is the same according to the magnitude of the vertical velocity. In the summer of 2017 (June, July), a wind vector calculation algorithm by Bragg scattering and Rayleigh scattering was developed using Changwon wind profiler data, and verified by comparing it with radiosonde data at 6 hour intervals.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1049-1056
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• 2023

The height of the atmospheric boundary layer indicates the peak developed when turbulence is generated by mixing heat and water vapor, and is generally determined through thermodynamic methods. Wind profilers produce atmospheric information from the scattering of signals sent into the atmosphere. A method for making the spectrum of turbulent components, turbulent kinetic energy dissipation rate, and refractive index structure coefficient was presented to determine the atmospheric boundary layer depth. Compared with the vertical distribution characteristics of potential temperature and specific humidity based on radiosonde data, the determination method of the atmospheric boundary layer height from wind profiler output was evaluated as very useful.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.481-494
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• 2018

The accurate radiative transfer model simulation is essential for an accurate ozone profile retrieval using optimal estimation from backscattered ultraviolet (BUV) measurement. The input parameters of the radiative transfer model are the main factors that determine the model accuracy. In particular, meteorological parameters such as temperature and surface pressure have a direct effect on simulating radiation spectrum as a component for calculating ozone absorption cross section and Rayleigh scattering. Hence, a sensitivity of UV ozone profile retrievals to these parameters has been investigated using radiative transfer model. The surface pressure shows an average error within 100 hPa in the daily / monthly climatological data based on the numerical weather prediction model, and the calculated ozone retrieval error is less than 0.2 DU for each layer. On the other hand, the temperature shows an error of 1-7K depending on the observation station and altitude for the same daily / monthly climatological data, and the calculated ozone retrieval error is about 4 DU for each layer. These results can help to understand the obtained vertical ozone information from satellite. In addition, they are expected to be used effectively in selecting the meteorological input data and establishing the system design direction in the process of applying the algorithm to satellite operation.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1211-1220
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• 2020

This research detects the features of the bright band (BB) through analysis of the vertical profile of range height indicator (RHI) and the slant range beam profile of plane position indicator (PPI) of the polarimetric radar measurements-horizontal reflectivity (ZH), differential reflectivity (ZDR), and cross-correlation coefficient (ρHV). As a result of the analysis, it is possible to clearly detect the bright band using the polarimetric radar measurements, and it is confirmed that the result is consistent by double searching for the BB using the RHI and PPI scan data at the same time. Based on these results, the accuracy of QPE (quantification of precipitation estimation) can be improved by applying the BB search method by the PPI slant range in this research to large rainfall radars that only scan PPI volumes in the field without RHI observations.