• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.285-291
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• 2011

Accurate assessment of the water and energy cycles is essential to understand hydrologic, climatologic, and ecological processes. Common Land Model (CLM) is one of the well-developed Soil-Vegetation-Atmosphere Transfer (SVAT) models based on the water and energy balance equation for accurate prediction of hydro-environmental cycles. The CLM can estimate realistic and reliable results using relatively simple parameters. It has been widely used in the world, however in Korea practical applications of the CLM are rare due to lack of information and input data. In this study, the CLM with Korea Flux network (KoFlux) and Kore Land Data Assimilation System (KLDAS) data were individually validated for domestic applications. This study showed that all comparisons between observations and model results from KoFlux and KLDAS had reasonable correlation with determination coefficient of 0.73~1.00 via regression. The results confirmed the applicability of the CLM and the possibility of the KLDAS usage for the region where input data are not existed.

• Journal of the Korean earth science society
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• v.35 no.4
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• pp.215-224
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• 2014

Data assimilation effect of mobile rawinsonde observation was evaluated using Unified Model (UM) with a Three-Dimensional Variational (3DVAR) data assimilation system during the intensive observation program of 2013 summer season (rainy season: 20 June-7 July 2013, heavy rain period: 8 July-30 July 2013). The analysis was performed by two sets of simulation experiments: (1) ConTroL experiment (CTL) with observation data provided by Korea Meteorological Administration (KMA) and (2) Observing System Experiment (OSE) including both KMA and mobile rawinsonde observation data. In the model verification during the rainy season, there were no distinctive differences for 500 hPa geopotential height, 850 hPa air temperature, and 300 hPa wind speed between CTL and OSE simulation due to data limitation (0000 and 1200 UTC only) at stationary rawinsonde stations. In contrast, precipitation verification using the hourly accumulated precipitation data of Automatic Synoptic Observation System (ASOS) showed that Equivalent Threat Score (ETS) of the OSE was improved by about 2% compared with that of the CTL. For cases having a positive effect of the OSE simulation, ETS of the OSE showed a significantly higher improvement (up to 41%) than that of the CTL. This estimation thus suggests that the use of mobile rawinsonde observation data using UM 3DVAR could be reasonable enough to assess the improvement of prediction accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

• Journal of Environmental Impact Assessment
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• v.11 no.2
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• pp.109-116
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• 2002

The diagnostic and prognostic methods for generating 3 dimensional wind field were comparatively analyzed and 4 dimensional data assimilation (FDDA) technique by incorporating Automatic Weather System (AWS) into the prognostic methods was discussed for the urban scale air quality model. The A WS covered the urban scale grid distance of 10.6 km and 4.3 km in South Korea and Kyong-in region, respectively. This is representing that AWS for FDDA could be fairly well accommodated in prognostic model with the meso${\gamma}$~ microa scale (~5 km), indicating that the 3 dimensional wind field by FDDA technique could be a useful interpretative tool in urban area for the atmospheric environmental impact assessment.

• Atmosphere
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• v.32 no.4
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• pp.395-409
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• 2022

A new soil moisture initialization scheme is applied to the Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6). It is designed to ingest the microwave soil moisture retrievals from Soil Moisture Active Passive (SMAP) radiometer using the Local Ensemble Transform Kalman Filter (LETKF). In this technical note, we describe the procedure of the newly-adopted initialization scheme, the change of soil moisture states by assimilation, and the forecast skill differences for the surface temperature and precipitation by GloSea6 simulation from two preliminary experiments. Based on a 4-year analysis experiment, the soil moisture from the land-surface model of current operational GloSea6 is found to be drier generally comparing to SMAP observation. LETKF data assimilation shows a tendency toward being wet globally, especially in arid area such as deserts and Tibetan Plateau. Also, it increases soil moisture analysis increments in most soil levels of wetness in land than current operation. The other experiment of GloSea6 forecast with application of the new initialization system for the heat wave case in 2020 summer shows that the memory of soil moisture anomalies obtained by the new initialization system is persistent throughout the entire forecast period of three months. However, averaged forecast improvements are not substantial and mixed over Eurasia during the period of forecast: forecast skill for the precipitation improved slightly but for the surface air temperature rather degraded. Our preliminary results suggest that additional elaborate developments in the soil moisture initialization are still required to improve overall forecast skills.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.910-919
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• 2012

The role of inorganic nitrogen assimilation in the production of amino acids, organic acids and soluble sugars is one of the most important biochemical processes in plants, and, in order to achieve normally, nitrate uptake and assimilation is essential. For this reason, the characterization of nitrate assimilation and metabolite composition from leaves, roots and xylem sap of tomato (Solanum lycopersicum) was investigated under different nitrate levels in media. Tomato plants were grown hydroponically in liquid culture under five different nitrate regimes: deficient (0.25 and 0.75 mM $NO_3{^-}$), normal (2.5 mM $NO_3{^-}$) and excessive (5.0 and 10.0 mM $NO_3{^-}$). All samples, leaves, roots and xylem sap, were collected after 7 and 14 days after treatment. The levels of amino acids, soluble sugars and organic acids were significantly decreased by N-deficiency whereas, interestingly, they remained higher in xylem sap as compared with N-normal and -surplus. The N-excessive condition did not exert any significant changes in metabolites composition, and thus their levels were similar with N-normal. The gene expression and enzyme activity of nitrate reductase (NR), nitrite reductase (NIR) and glutamine synthetase (GS) were greatly influenced by nitrate. The data presented here suggest that metabolites, as a signal messenger, existed in xylem sap seem to play a crucial role to acquire nitrate, and, in addition, an increase in ${\alpha}$-ketoglutarate pathway-derived amino acids under N-deficiency may help to better understand plant C/N metabolism.

• Phonetics and Speech Sciences
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• v.7 no.2
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• pp.19-28
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• 2015

This study investigated final consonant error characteristics at word-medial position in children with functional articulation disorder. Data was collected from 11 children with functional articulation and 11 normal children, ages 4 to 5. The speech samples were collected from a naming test. Seventy-five words with every possible bi-consonants matrix at the word-medial position were used. The results of this study were as follows : First, percentage of correct word-medial final consonants of functional articulation disorder was lower than normal children. Second, there were significant differences between two groups in omission, substitution and assimilation error. Children with functional articulation disorder showed a high frequency of omission and regressive assimilation error, especially alveolarization in regressive assimilation error most. However, normal children showed a high frequency of regressive assimilation error, especially bilabialization in regressive assimilation error most. Finally, the results of error analysis according to articulation manner, articulation place and phonation type of consonants of initial consonant at word-medial, both functional articulation disorder and normal children showed a high error rate in stop sound-stop sound condition. The error rate of final consonant at word-medial position was high when initial consonant at word-medial position was alveolar sound and alveopalatal sound. Futhermore, when initial sounds were fortis and aspirated sounds, more errors occurred than linis sound was initial sound. The results of this study provided practical error characteristics of final consonant at word-medial position in children with speech sound disorder.

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• Atmosphere
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• v.23 no.2
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• pp.171-186
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• 2013

Recently, the number of observations used in a data assimilation system is increasing due to the enormous amount of observations, including satellite data. However, it is not clear that all of these observations are always beneficial to the performance of the numerical weather prediction (NWP). Therefore, it is important to evaluate the effect of observations on these forecasts so that the observations can be used more usefully in NWP process. In this study, the adjoint-based Forecast Sensitivity to Observation (FSO) method with the KMA Unified Model (UM) is applied to two high-impact weather events which occurred in summer and winter in Korea in an effort to investigate the effects of observations on the forecasts of these events. The total dry energy norm is used as a response function to calculate the adjoint sensitivity. For the summer case, TEMP observations have the greatest total impact while BOGUS shows the greatest impact per observation for all of the 24-, 36-, and 48-hour forecasts. For the winter case, aircraft, ATOVS, and ESA have the greatest total impact for the 24-, 36-, and 48-hour forecasts respectively, while ESA has the greatest impact per observation. Most of the observation effects are horizontally located upwind or in the vicinity of the Korean peninsula. The fraction of beneficial observations is less than 50%, which is less than the results in previous studies. As an additional experiment, the total moist energy norm is used as a response function to measure the sensitivity of 24-hour forecast error to observations. The characteristics of the observation impact with the moist energy response function are generally similar to those with the dry energy response function. However, the ATOVS observations were found to be sensitive to the response function, showing a positive (a negative) effect on the forecast when using the dry (moist) norm for the summer case. For the winter case, the dry and moist energy norm experiments show very similar results because the adjoint of KMA UM does not calculate the specific humidity of ice properly such that the dry and moist energy norms are very similar except for the humidity in air that is very low in winter.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.745-757
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• 2006

We focus on the improvement of accuracy of sea surface wind over complex coastal area doling the warm season. Local Analysis Prediction System (LAPS) was used to improve the initial values in Mesoscale Meteorological model (MM5). During the clear summer days with weak wind speed, sea surface wind simulated with LAPS was compared with the case without LAPS. The results of modeling with LAPS has a good agreement mesoscale circulation such as mountain and valley winds on land and in case of modeling without LAPS, wind speed overestimated over the sea in the daytime. And the results of simulation with LAPS indicated similar wind speed values to observational data over the sea under influence of data assimilation using BUOY, QuikSCAT, and AMEBAS. The present study suggests that MM5 modelling with LAPS showed more improved results than that of without LAPS to simulate sea surface wind over the complex coastal area.