• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.25-28
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• 2016

Recently, because of the weather forecasts through the low-resolution data has been limited, the demand of the high-resolution data is sharply increasing. Therefore, in this study, we restore the ultra-high resolution synthetic precipitation and temperature data for 2000-2014 due to small-scale topographic effect using the QPM (Quantitative Precipitation Model)/QTM (Quantitative Temperature Model). First, we reproduce the detailed precipitation and temperature data with 1km resolution using the distribution of Automatic Weather System (AWS) data and Automatic Synoptic Observation System (ASOS) data, which is about 10km resolution with irregular grid over South Korea. Also, we recover the precipitation and temperature data with 1km resolution using the MERRA reanalysis data over North Korea, because there are insufficient observation data. The precipitation and temperature from restored current climate reflect more detailed topographic effect than irregular AWS/ASOS data and MERRA reanalysis data over the Korean peninsula. Based on this analysis, more detailed prospect of regional climate is investigated.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Atmosphere
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• v.18 no.4
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• pp.387-395
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• 2008

The impact of horizontal resolution on a regional climate model was investigated by simulating precipitation over the Korean Peninsula. As a regional climate model, the SNURCM(Seoul National University Regional Climate Model) has 21 sigma layers and includes the NCAR CLM(National Center for Atmospheric Research Community Land Model) for land-surface model, the Grell scheme for cumulus convection, the Simple Ice scheme for explicit moisture, and the MRF(Medium-Range Forecast) scheme for PBL(Planetary Boundary Layer) processing. The SNURCM was performed with 20 km resolution for Korea and 60 km resolution for East Asia during a 20-year period (1980-1999). Although the SNURCM systematically underestimated precipitation over the Korean Peninsula, the increase of model resolution simulated more precipitation in the southern region of the Korean Peninsula, and a more accurate distribution of precipitation by reflecting the effect of topography. The increase of precipitation was produced by more detailed terrain data which has a 10 minute terrain in the 20 km resolution model compared to the 30 minute terrain in the 60 km resolution model. The increase in model resolution and more detailed terrain data played an important role in generating more precipitation over the Korean Peninsula. While the high resolution model with the same terrain data resulted in increasing of precipitation over the Korean Peninsula including the adjoining sea, the difference of the terrain data resolution only influenced the precipitation distribution of the mountainous area by increasing the amount of non-convective rain. In conclusion, the regional climate model (SNURCM) with higher resolution simulated more precipitation over the Korean Peninsula by reducing the systematic underestimation of precipitation over the Korean Peninsula.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.571-581
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• 2015

Soil moisture content is generally accepted as an important factor to understand the process of crop growth and is the basis of earth system models for analysis and prediction of the crop condition. To continuously monitor soil moisture changes at kilometer scale, it is demanded to create high resolution data from the current, several tens of kilometers. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) from 10 km to 30 m resolution using a soil texture and field measurements that have a high correlation with the SMC. As a result, the soil moisture variations of both data (before and after downscaling) were identical, and the Root Mean Square Error (RMSE) of SMC exhibited the low values. Also, time series analyses showed that three kinds of SMC data (field measurement, original AMSR2, and downscaled AMSR2) had very similar temporal variations. Our method can be applied to downscaling of other soil variables and can contribute to monitoring small-scale changes of soil moisture by providing high resolution data.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.379-379
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• 2020

The influence of drought has increased due to global warming. In addition, forest fires have occurred more frequently due to droughts and resulted in property losses and casualty. In this study, the effects of drought on Goseong-Sokcho Forest Fire in 2019 were analyzed using high-resolution synthetic precipitation data. In order to determine the severity of drought, the average, 20%tile and 80%ile values were calculated using the synthetic precipitation data of the past 30 years and compared with the current climatology. We have investigated the multi-year accumulated precipitation data to determine the persistence of drought. In Goseong-Sokcho forest fire case, the two-year cumulative synthetic precipitation data shows a similar value to the climate, but the three-year cumulative synthetic precipitation data was close to the 20%ile lines of the climate value. It may expose that the shortage of precipitation in 2017 had persisted until 2019, despite abundant precipitation during the summer in 2018. Therefore, Goseong-Sokcho forest fire might be spread more rapidly by drought which has been persisted since 2017.

• Journal of Environmental Science International
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• v.15 no.12
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• pp.1141-1154
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• 2006

Orographic effect is one of the important factors to induce Local circulations and to make atmospheric turbulence, so it is necessary to use the exact topographic data for prediction of local circulations. In order to clarify the sensitivity of the spatial resolution of topography data, numerical simulations using several topography data with different spatial resolution are carried out under stable and unstable synoptic conditions. The results are as follows: 1) Influence of topographic data resolution on local circulation tends to be stronger at simulation with fine grid than that with coarse grid. 2) The hight of mountains in numerical model become mote reasonable with high resolution topographic data, so the orographic effect is also emphasized and clarified when the topographic data resolution is higher. 2) The higher the topographic resolution is, the stronger the mountain effect is. When used topographic data resolution become fine, topography in numerical model becomes closer to real topography. 3) The topographic effect tends to be stronger when atmospheric stability is strong stable. 4) Although spatial resolution of topographic data is not fundamental factor for dramatic improvement of weather prediction accuracy, some influence on small scale circulation can be recognized, especially in fluid dynamic simulation.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.20-27
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• 2011

A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.164-173
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• 2017

Alternative cropping systems would be one of climate change adaptation options. Suitable areas for a crop could be identified using a climate suitability model. The EcoCrop model has been used to assess climate suitability of crops using monthly climate surfaces, e.g., the digital climate map at high spatial resolution. Still, a high-performance computing approach would be needed for assessment of climate suitability to take into account a complex terrain in Korea, which requires considerably large climate data sets. The objectives of this study were to implement a script for R, which is an open source statistics analysis platform, in order to use the EcoCrop model under a parallel computing environment and to assess climate suitability of maize using digital climate maps at high spatial resolution, e.g., 1 km. The total running time reduced as the number of CPU (Central Processing Unit) core increased although the speedup with increasing number of CPU cores was not linear. For example, the wall clock time for assessing climate suitability index at 1 km spatial resolution reduced by 90% with 16 CPU cores. However, it took about 1.5 time to compute climate suitability index compared with a theoretical time for the given number of CPU. Implementation of climate suitability assessment system based on the MPI (Message Passing Interface) would allow support for the digital climate map at ultra-high spatial resolution, e.g., 30m, which would help site-specific design of cropping system for climate change adaptation.

• Journal of Environmental Science International
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• v.13 no.10
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• pp.891-902
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• 2004

In order to predict air pollution and Yellow-sand dispersion precisely, it is necessary to clarify the sensitivity of meteorological field input interval. Therefore numerical experiment by atmospheric dynamic model(RAMS) and atmospheric dispersion model(PDAS) was performed for evaluating the effect of temporal and spatial resolution of meteorological data on particle dispersion. The results are as follows: 1) Base on the result of RAMS simulation, surface wind direction and speed can either synchronize upper wind or not. If surface wind and upper wind do not synchronize, precise prediction of Yellow-sand dispersion is strongly associated with upwelling process of sand of particle. 2) There is no significant discrepance in distribution of particle under usage of difference temporal resolution of meteorological information at early time of simulation, but the difference of distribution of particles become large as time goes by. 3) There is little difference between calculated particles distributions in dispersion experiments with high temporal resolution of meteorological data. On the other hand, low resolution of meteorological data occur the quantitative difference of particle density and there is strong tendency to the quantitative difference.

• Journal of Korea Water Resources Association
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• v.40 no.3
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• pp.191-204
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• 2007

To evaluate the climate change impacts on water resources, this study generates and analyzes the climate change scenarios for 139 sub-basins in Korea using high resolution ($27km\;{\times}\; 27km$) SHES A2 scenario and LARS-WG. The $27km\;{\times}\; 27km$ high resolution NCAR/PSU MM5 scenario is downscaled from 350km horizontal resolution ECHO-G data. The A2 scenario relatively well reproduced Korean spatial precipitation characteristics, but it underestimated the precipitation over the Han River and the Gum River basins. The LARS-WG was selected and evaluated to overcome the limitation of climate model and to create a highly reliable climate scenario. The results show that the monthly mean minimum and maximum temperature and monthly mean precipitation are within ${\pm}20%$ from the observed mean, and ${\pm}50%$ from the standard deviation that represents the generated data are highly reliable. Moreover, the comparison results between observed data and generated data from LARS-WG show that the latter can reflect the regional climate characteristic very well that can not be simulated from the former.