• Atmosphere
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• v.33 no.5
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• pp.441-456
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• 2023

The mobile observation method, in which a meteorological drone observes while ascending, can observe the vertical profile of wind at 1 m-interval. In addition, since continuous flights are possible at time intervals of less than 30 minutes, high-resolution observation data can be obtained both spatially and temporally. In this study, we verify the accuracy of mobile observation data from meteorological drone (drone) and fill the spatio-temporal observation gaps in the lower atmosphere. To verify the accuracy of mobile observation data observed by drone, it was compared with rawinsonde observation data. The correlation coefficients between two equipment for a wind speed and direction were 0.89 and 0.91, and the root mean square errors were 0.7 m s^-1 and 20.93°. Therefore, it was judged that the drone was suitable for observing vertical profile of the wind using mobile observation method. In addition, we attempted to resolve the observation gaps in the lower atmosphere. First, the vertical observation gaps of the wind profiler between the ground and the 150 m altitude could be resolved by wind observation data using the drone. Secondly, the temporal observation gaps between 3-hour interval in the rawinsonde was resolved through a drone observation case conducted in Taean-gun, Chungcheongnam-do on October 13, 2022. In this case, the drone mobile observation data every 30-minute intervals could observe the low-level jet more detail than the rawinsonde observation data. These results show that the mobile observation data of the drone can be used to fill the spatio-temporal observation gaps in the lower atmosphere.

• Atmosphere
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• v.33 no.1
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• pp.33-47
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• 2023

In this study, for the application of observation errors to the Korean Integrated Model (KIM) to utilize the Constellation Observing System for Meteorology, Ionosphere & Climate-2 (COSMIC-2) new satellites, the observation errors were diagnosed based on the Desroziers method using the cost function in the process of variational data assimilation. We calculated observation errors for all observational species being utilized for KIM and compared with their relative values. The observation error of the calculated the Global Navigation Satellite System Radio Occultation (GNSS RO) was about six times smaller than that of other satellites. In order to balance with other satellites, we conducted two experiments in which the GNSS RO data expanded by about twice the observation error. The performance of the analysis field was significantly improved in the tropics, where the COSMIC-2 data are more available, and in the Southern Hemisphere, where the influence of GNSS RO data is significantly greater. In particular, the prediction performance of the Southern Hemisphere was improved by doubling the observation error in global region, rather than doubling the COSMIC-2 data only in areas with high density, which seems to have been balanced with other observations.

• Proceedings of the KSRS Conference
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• v.1
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• pp.228-231
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• 2006

In this paper, requirements of Meteorological Administration about Meteorological Imager (MI) of Communications, Ocean and Meteorological Satellite (COMS) is analyzed for the design of COMS ground station and according to the analysis results, the distribution image size of each observation area suitable for satellite Field Of View (FOV) stated at the requirements of meteorological administration is determined and the precise satellite FOV and the size of distribution image is calculated on the basis of the image size of the determined observation area. The results in this paper were applied to the detailed design for COMS ground station and also are expected to be used for the future observation scheduling and the scheduling of distribution of user data.

• Atmosphere
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• v.33 no.5
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• pp.561-570
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• 2023

In order to improve the predictability of marine high-impacts weather such as typhoon and high waves, the marine observation network is an essential because it could be rapidly changed by strong air-sea interaction. In this regard, the National Institute of Meteorological Sciences, Korea Meteorological Administration (NIMS/KMA) has promoted the Argo float observation program since 2001 to participate in the International Argo program. In this study, current status and future direction of the NIMS/KMA Argo program are presented through the internal meeting and external expert forum. To date, a total of 264 Argo floats have been deployed into the offshore around the Korean Peninsula and the Northwestern Pacific Ocean. The real-time and delayed modes quality control (QC) system of Argo data was developed, and an official regional data assembling center (call-sign 'KM') was run. In 2002, the Argo homepage was established for the systematic management and dissemination of Argo data for domestic and international users. The future goal of the NIMS/KMA Argo program is to improve response to the marine high-impacts weather through a marine environment monitoring and observing system. The promotion strategy for this is divided into four areas: strengthening policy communication, developing observation strategies, promoting utilization research, and activating international cooperation.

• Atmosphere
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• v.18 no.4
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• pp.299-316
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• 2008

The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.

• Atmosphere
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• v.17 no.4
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• pp.435-453
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• 2007

KEOP (Korea Enhanced Observing Period)-2004 intensive summer observation was carried out from 20 June to 5 July 2004 over the Southwestern part of the Korean peninsula. In this study, the effects of KEOP-2004 intensive observation data on the simulation of precipitation system are investigated using KLAPS (Korea Local Analysis and Prediction System) and PSU/NCAR MM5. Three precipitation cases during the intensive observation are selected for detailed analysis. In addition to the control experiments using the traditional data for its initial and boundary conditions, two sensitivity experiments using KEOP data with and without Jindo radar are performed. Although it is hard to find a clear and consistent improvement in the verification score (threat score), it is found that the KEOP data play a role in improving the position and intensity of the simulated precipitation system. The experiments started at 00 and 12 UTC show more positive effect than those of 06 and 18 UTC. The effect of Jindo radar is dependent on the case. It plays a significant role in the heavy rain cases related to a mesoscale low over Changma front and the landing of a Typhoon. KEOP data produce more strong difference in the 06/18 UTC experiments than in 00/12 UTC, but give more positive effects in 00/12 UTC experiments. One of the possible explanations for this is that : KEOP data could properly correct the atmosphere around them when there are certain amounts of data, while gives excessive effect to the atmospheric field when there are few data. CRA analysis supports this reasoning. According to the CRA (Contiguous Rain Area) analysis, KEOP data in 00/12 UTC experiments improve only the surrounding area, resulting in essentially same precipitation system so the effects remain only in each convective cell rather than the system itself. On the other hand, KEOP data modify the precipitation system itself in 06/18 UTC experiments. Therefore the effects become amplified with time integration.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.27-33
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• 2014

To well design the solar energy system using solar energy, the correlation to calculate solar irradiation is basically needed. So, this study was performed to reveal the relationships between the solar irradiation and four meteorological observation data(dry bulb temperature, relative humidity, sunshine duration, and cloud cover) which are different from previous other researches. And then, we finally proposed the first order non-linear correlation from the measured solar irradiation using four meteorological observation data with MINITAB. To show the deviation of the solar irradiation between measured and calculated, this study compared using the daily total solar irradiance and the maximum peak value. From those results, the calculation error was estimated about maximum 25.4% for the daily total solar irradiance. The error of the solar irradiation between measured and calculated was made from the curve fitting error. So, solar irradiation prediction correlation with higher accuracy can be obtained using 2nd or higher order terms with four meteorological observation data.

• Journal of Astronomy and Space Sciences
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• v.33 no.2
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• pp.137-146
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• 2016

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.132-134
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• 1999

Rainfall characteristics for designing the optimum millimeter-wave communication systems from two rainfall data set was analyzed. Two rainfall data sets were compared; one-minute rainfall rate data, one-hour synoptic observation data. Each data set has different observation method, sampling frequency. We looked for tendency and quality confluence between two data sets. We showed several results using one-minute rainfall data by millimeter-wave attenuation model. A climatological one-minute rainfall rate data set over Korean Peninsula will be made after data quality control procedure

• Atmosphere
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• v.31 no.3
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• pp.311-326
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• 2021

To improve the predictability of high-impact weather phenomena around Seoul, where a larger number of people are densely populated, KMA conducted the intensive observation from 22 June to 20 September in 2020 over the Seoul area. During the intensive observation period (IOP), the dropsonde from NIMS Atmospheric Research Aircraft (NARA) and the radiosonde from KMA research vessel Gisang1 were observed in the Yellow Sea, while, in the land, the radiosonde observation data were collected from Icheon and Incheon. Therefore, in this study, the effects of radiosonde and dropsonde data during the IOP were investigated by Observing System Experiment (OSE) based on Korean Integrated Model (KIM). We conducted two experiments: CTL assimilated the operational fifteen kinds of observations, and EXP assimilated not only operational observation data but also intensive observation data. Verifications over the Korean Peninsula area of two experiments were performed against analysis and observation data. The results showed that the predictability of short-range forecast (1~2 day) was improved for geopotential height at middle level and temperature at lower level. In three precipitation cases, EXP improved the distribution of precipitation against CTL. In typhoon cases, the predictability of EXP for typhoon track was better than CTL, although both experiments simulated weaker intensity as compared with the observed data.