• Journal of Environmental Science International
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• v.32 no.11
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• pp.841-852
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• 2023

In this study, the significant wave height and wave period of a specially designed observation system that connected two drifting buoys to an ocean data buoy was observed for 23 days from February 7 to 29, 2020, and the results were compared and analyzed. The results indicated that, in comparison to the ocean data buoy, the drifting buoy exhibited greater variability in significant wave height over shorter time intervals. The wave period of the ocean data buoy also appeared longer than that of the drifting buoy. The greater the observed significant wave height and wave period from both the ocean data and drifting buoys, the more pronounced the differences between the two observation instruments become. Moreover, the study revealed that the disparity in observation methods between the ocean data and drifting buoys did not significantly affect the significant wave height characteristics, as long as the period remained unchanged for up to half of the observation time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.117-127
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• 2020

The Early Warning System for agrometeorological hazard of the Rural Development Administration (Korea) forecasts detailed weather for each farm based on the meteorological information provided by the Korea Meteorological Administration, and estimates the growth of crops and predicts a meteorological hazard that can occur during the growing period by using the estimated detailed meteorological information. For verification of early warning system, automated weather observation network was constructed in the study area. Moreover, a real-time web display system was built to deliver near real-time weather data collected from the observation network. The meteorological observation system collected diverse meteorological variables including temperature, humidity, solar radiation, rainfall, soil moisture, sunshine duration, wind velocity, and wind direction. These elements were collected every minute and transmitted to the server every ten minutes. The data display system is composed of three phases: the first phase builds a database of meteorological data collected from the meteorological observation system every minute; the second phase statistically analyzes the collected meteorological data at ten-minutes, one-hour, or one-day time step; and the third phase displays the collected and analyzed meteorological data on the web. The meteorological data collected in the database can be inquired through the webpage for all data points or one data point in the unit of one minute, ten minutes, one hour, or one day. Moreover, the data can be downloaded in CSV format.

• Atmosphere
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• v.21 no.3
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• pp.319-336
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• 2011

The objective of this study was to assess the meteorological capability of Korea by comparing with that of the U.S. and Japan as of 2010. The research was conducted based on various indices and surveys, and quantified the results using the Gordon's scoring model. The index assessment used 11 items derived from 9 segments - surface observation, advanced observation and observations quality in the observation field; data assimilation, numerical model and infrastructure in the data processing field; forecast accuracy in the forecast field; climate prediction and climate change in the climate field - in this research, we classified the meteorological technology into four fields. In the survey assessment, another 10 items in addition to the above 11 ones (total 21 items) were used. In the field of climate, Korea was found to lag far behind the U.S. (96.5p) and Japan (90.5p) with 77.6 points out of 100, which is 18.9 and 12.9 points lower than them respectively. On the other hand, Korea showed the narrowest gap with Japan (95.3p) and the U.S. (94.2) in the forecasting field, recording 90.3 points. Particularly, in surface observation, infrastructure and forecast accuracy segment, Korea was on a par with the U.S. and Japan, boasting 100.5 percent compared to their counterparts. However, in advanced observation, data quality and climate change segment, Korea was only at the level of 81.5 percent compared to that of the U.S. and Japan. All in all, the technological prowess of Korea, scoring 84.6 points, stood at 89.7 percent of that of the U.S. (94.3p) and 91.9 percent of Japan (92.1p).

• Atmosphere
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• v.34 no.1
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• pp.69-81
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• 2024

In this paper, Annual flux variations in the Boseong Tall Tower (BTT) from 2016 to 2020 were analyzed using data from three levels (2.5 m, 60 m, and 300 m). BTT was installed in Boseong-gun, Jeollanam-do in February 2014 and continued to conduct energy exchange observations such as CO2, sensible heat, and latent heat using the eddy covariance method until March 2023. The BTT was located in a very flat and uniform paddy field, and flux observations were conducted at four levels: 2.5 m, 60 m, 140 m, and 300 m above ground. Surface energy balance was confirmed from observed data of net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. Additionally, 2.5 m height surface fluxes, which are most influenced by agricultural land, were compared with data from Local Data Assimilation and Prediction System (LDAPS) of the Korea Meteorological Administration to evaluate the accuracy of LDAPS flux data. The correlation coefficient between LDAPS flux data and observed values was 0.95 or higher. Excluding summer latent heat flux data, there was a general tendency for LDAPS data to be higher than observed values. The footprint areas estimated below 60 m height mainly covered agricultural land, and flux observations at 2.5 m and 60 m heights showed typical agricultural characteristics. In contrast, the footprint estimated at 300 m height did not show agricultural characteristics, indicating that observations at this height encompassed a wide range, including mountains, sea, and roads. The analysis results of long-term flux observations can contribute to understanding the energy and carbon dioxide fluxes in agricultural fields. Furthermore, these results can be utilized as essential data for validating and improving numerical models related to such fluxes.

• Atmosphere
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• v.27 no.3
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• pp.359-370
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• 2017

In this study, the oceanic Total Precipitable Water (TPW) retrieval algorithm at 16 km altitude of High Altitude Long Endurance Unmanned Aerial Vehicle (HALE UAV) is described. Empirical equation based on Wentz method (1995) that uses the 18.7 and 22.235 GHz channels is developed using the simulated brightness temperature and SeeBor training dataset. To do radiative simulation, Satellite Data Simulator Unit (SDSU) Radiative Transfer Model (RTM) is used. The data of 60% (523) and 40% (349) in the SeeBor training dataset are used to develop and validate the TPW retrieval algorithm, respectively. The range of coefficients for the TPW retrieval at the altitude of 3~18 km with 3 km interval were 153.69~199.87 (${\alpha}$), 54.330~58.468 (${\beta}$), and 84.519~93.484 (${\gamma}$). The bias and RMSE at each altitude were found to be about $-0.81kg\;m^{-2}$ and $2.17kg\;m^{-2}$, respectively. Correlation coefficients were more than 0.9. Radiosonde observation has been generally operated over land. To validate the accuracy of the oceanic TPW retrieval algorithm, observation data from the Korea Meteorological Administration (KMA) Gisang 1 research vessel about six clear sky cases representing spring, autumn, and summer season is used. Difference between retrieved and observed TPW at 16 km altitude were in the range of $0.53{\sim}1.87kg\;m^{-2}$, which is reasonable for most applications. Difference in TPW between retrieval and observation at each altitude (3~15 km) is also presented. Differences of TPW at altitudes more than 6 km were $0.3{\sim}1.9kg\;m^{-2}$. Retrieved TPW at 3 km altitude was smaller than upper level with a difference of $-0.25{\sim}0.75kg\;m^{-2}$ compared to the observed TPW.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1141-1154
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• 2018

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

• Atmosphere
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• v.14 no.1
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• pp.4-23
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• 2004

To monitor the world's oceans and understand the role of the oceans for climate change, an Array for Real-time Geostrophic Oceanography (ARGO) program has been carried out since year 2000. Autonomous profiling floats of about 820 are reporting the vertical temperature, salinity, and pressure profiles of the upper 2000 m underwater at regular time intervals. Meteorological Research Institute (METRI) of Korea Meteorological Administration (KMA) launched 45 floats at the East Sea and the western Pacific to understand characteristics of water properties and develop the global ocean observation system as a part of international cooperation project. In this study, we introduce ARGO program, METRI-ARGO and the features of APEX float itself and their data formats. We also describe the significant points to be considered for using ARGO data.

• Atmosphere
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• v.28 no.4
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• pp.369-382
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• 2018

Planetary boundary layer height (PBLH), produced by the Local Data Assimilation and Prediction System (LDAPS), was verified using RawinSonde (RS) data obtained from observation at Daegwallyeong (DGW) and Sokcho (SCW) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). The PBLH was calculated using RS data by applying the bulk Richardson number and the parcel method. This calculated PBLH was then compared to the values produced by LDAPS. The PBLH simulations for DGW and SCW were generally underestimation. However, the PBLH was an overestimation from surface to 200 m and 450 m at DGW and SCW, respectively; this result of model's failure to correctly simulate the Surface Boundary Layer (SBL) and the Mixing Layer (ML) as the PBLH. When the accuracy of the PBLH simulation is low, large errors are seen in the mid- and low-level humidity. The highest frequencies of Planetary boundary layer (PBL) types, calculated by the LDAPS at DGW and SCW, were presented as types Ι and II, respectively. Analysis of meteorological factors according to the PBL types indicate that the PBLH of the existing stratocumulus were overestimated when the mid- and low-level humidity errors were large. If the instabilities of the surface and vertical mixing into clouds are considered important factors affecting the estimation of PBLH into model, then mid- and low-level humidity should also be considered important factors influencing PBLH simulation performance.

• Atmosphere
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• v.30 no.1
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• pp.31-46
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• 2020

The aircraft observation campaign was performed to investigate thermodynamic conditions of snowfall cloud over the East Sea of Korean peninsula from 2 February to 16 March 2018. During this period, four snowfall events occurred in the Yeongdong region and three cases were analyzed using dropsonde data. Snowfall cases were associated with the passage of southern low-pressure (maritime warm air mass) and expansion of northern high-pressure (continental polar air mass). Case 1 and Case 2a were related to low-pressure systems, and Case 2b and Case 3 were connected with high-pressure systems, respectively. And their thermodynamic properties and horizontal distribution of snowfall cloud were differed according to the influence of the synoptic condition. In Case 1 and Case 2a, atmospheric layers between sea surface and 350 hPa contained moisture more than 15 mm of TPW with multiple inversion layers detected by dropsonde data, while the vertical atmosphere of Case 2b and Case 3 were dry as TPW 5 mm or less with a single inversion inversion layer around 750~850 hPa. However, the vertical distributions of equivalent potential temperature (θ_e) were similar as moist-adiabatically neutral condition regardless of the case. But, their values below 900 hPa were about 10 K higher in Case 1 and Case 2a (285~290 K) than in Case 2b and Case 3 (275~280 K). The difference in these values is related to the characteristics of the incoming air mass and the location of the snowfall cloud.

• Atmosphere
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• v.29 no.4
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• pp.439-450
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• 2019

Present weather plays an important role not only for atmospheric sciences but also for public welfare and road safety. While the widely used state-of-the-art visibility and present weather sensor yields present weather, a single type of measurement is far from perfect to replace long history of human-eye based observation. Truly automatic present weather observation enables us to increase spatial resolution by an order of magnitude with existing facilities in Korea. 8 years of human-eyed present weather records in 19 sites over Korea are compared with visibility sensors and auxiliary measurements, such as humidity of AWS. As clear condition agrees with high probability, next best categories follow fog, rain, snow, mist, haze and drizzle in comparison with human-eyed observation. Fog, mist and haze are often confused due to nature of machine sensing visibility. Such ambiguous weather conditions are improved with empirically induced criteria in combination with visibility and humidity. Differences between instrument manufacturers are also found indicating nonstandard present weather decision. Analysis shows manufacturer dependent present weather differences are induced by manufacturer's own algorithms, not by visibility measurement. Accuracies of present weather for haze, mist, and fog are all improved by 61.5%, 44.9%, and 26.9% respectively. The result shows that automatic present weather sensing is feasible for operational purpose with minimal human interactions if appropriate algorithm is applied. Further study is ongoing for impact of different sensing types between manufacturers for both visibility and present weather data.