• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• Journal of the Mineralogical Society of Korea
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• v.10 no.1
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• pp.18-32
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• 1997

Analysis of geological data, relating to occurrence and formation of diamonds as well as host rocks, inclined author to have different outlook on the diamond genesis and to establish a proposition on their formation at pneumatolytic-hydrothermal conditions near superficial Earth zones. Based on that theoretical foundations and experimental works, the first low-pressure and low-temperature hydrothermal diamond synthesis from water solution in pressure autoclave was executed. As a result, the natural diamond seed crystal grew bigger ad coupling of the synthetic diamond single-crystalline grains were obtained. SEM documentation proofs that parallely paragenetic crystallization of quartz and diamond, and nucleation of new octahedral diamond crystals brush take place on the seed crystal surface. Forecast of none times growth of diamond industrial application at 2000 and seventeen times at 2010 with reference to 1995, needs technology of large and pure single-crystals diamond synthesis. Growth of the stable and destressed diamond single-crystals in the pseudo-metastable diamond plot, may be realized with processes going through the long time and with participation of free radicals catalysts admixtures only. Sol-gel colloidal processes are an example of environment which form stable crystals in thermodynamically unstable conditions through a long time. Paper critically discusses a whole way of studies on the diamond synthesis, from high-pressure and high-temperature processes through chemical vapour deposition up to hydrothermal experiments.

• Atmosphere
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• v.34 no.2
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• pp.107-121
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• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Atmosphere
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• v.34 no.3
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• pp.325-336
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• 2024

Radiosonde is an important in-situ profiling instrument that measures atmospheric temperature, moisture, and wind structure from the surface to the middle stratosphere. The operational radiosonde measurements are carried out more than twice (at 0000 UTC and 1200 UTC) daily at approximately 1,300 World Meteorological Organization (WMO) stations and play a pivotal role in daily weather forecasts. It also contributes to the monitoring of atmospheric structure by providing the key physical information like temperature and pressure, forming the backbone of atmospheric (re)analyses and numerical weather forecasts. Additionally, high-resolution radiosonde profiles are used for calibration and evaluation of satellite products. Despite these advantages, radiosonde measurements are mostly limited to operational uses due to the high initial cost of ground instrument setup required for data transmission and reception. This study outlines a cost-effective (roughly one-tenth of the operational cost) method for establishing the ground station and the necessary radiosonde measurement procedures, offering guidance for individual researchers or university-level instructors.

• Atmosphere
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• v.24 no.3
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• pp.283-301
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• 2014

In 2010, only 14 tropical cyclones (TCs) were generated over the western North Pacific (WNP), which was the smallest since 1951. This study summarizes characteristics of TCs generated in 2010 over the WNP and investigates the causes of the record-breaking TC genesis. A long-term variation of TC activity in the WNP and verification of official track forecast in 2010 are also examined. Monthly tropical sea surface temperature (SST) anomaly data reveal that El Ni$\tilde{n}$o/Southern Oscillation (ENSO) event in 2010 was shifted from El Ni$\tilde{n}$o to La Ni$\tilde{n}$a in June and the La Ni$\tilde{n}$a event was strong and continued to the end of the year. We found that these tropical environments leaded to unfavorable conditions for TC formation at main TC development area prior to May and at tropics east of $140^{\circ}E$ during summer mostly due to low SST, weak convection, and strong vertical wind shear in those areas. The similar ENSO event (in shifting time and La Ni$\tilde{n}$a intensity) also occurred in 1998, which was the second smallest TC genesis year (16 TCs) since 1951. The common point of the two years suggests that the ENSO episode shifting from El Ni$\tilde{n}$o to strong La Ni$\tilde{n}$a in summer leads to extremely low TC genesis during La Ni$\tilde{n}$a although more samples are needed for confidence. In 2010, three TCs, DIANMU (1004), KOMPASU (1007) and MALOU (1009), influenced the Korean Peninsula (KP) in spite of low total TC genesis. These TCs were all generated at high latitude above $20^{\circ}N$ and arrived over the KP in short time. Among them, KOMPASU (1007) brought the most serious damage to the KP due to strong wind. For 14 TCs in 2010, mean official track forecast error of the Korea Meteorological Administration (KMA) for 48 hours was 215 km, which was the highest among other foreign agencies although the errors are generally decreasing for last 10 years, suggesting that more efforts are needed to improve the forecast skill.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.469-483
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• 2006

An algorithm was developed to estimate stability indices (SI) over the Korean peninsula using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) infrared brightness temperatures (TBs). The SI is defined as the stability of the atmosphere in the hydrostatic equilibrium with respect to the vertical displacements and is used as an index for the potential severe storm development. Using atmosphere temperature and moisture profiles from Regional Data Assimilation and Prediction System (RDAPS) as initial guess data for a nonlinear physical relaxation method, K index (KI), KO Index (KO), lifted index (LI), and maximum buoyancy (MB) were estimated. A fast radiative transfer model, RTTOV-7, is utilized for reducing the computational burden related to the physical relaxation method. The estimated TBs from the radiative transfer simulation are in good agreement with observed MODIS TBs. To test usefulness for the short-term forecast of severe storms, the algorithm is applied to the rapidly developed convective storms. Compared with the SIs from the RDAPS forecasts and NASA products, the MODIS SI obtained in this research predicts the instability better over the pre-convection areas. Thus, it is expected that the nowcasting and short-term forecast can be improved by utilizing the algorithms developed in this study.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.557-577
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• 2023

This study defines non-precipitation information as areas with weak precipitation or cloud particles that radar cannot detect due to weak returned signals, and suggests methods for its utilization in data assimilation. Previous studies have demonstrated that assimilating radar data from precipitation echoes can produce precipitation in model analysis and improve subsequent precipitation forecast. However, this study also recognizes the non-precipitation information as valuable observation and seeks to assimilate it to suppress spurious precipitation in the model analysis and forecast. To incorporate non-precipitation information into data assimilation, we propose observation operators that convert radar non-precipitation information into hydrometeor mixing ratios and relative humidity for the Weather Research and Forecasting Data Assimilation system (WRFDA). We also suggest a preprocessing method for radar non-precipitation information. A single-observation experiment indicates that assimilating non-precipitation information fosters an environment conducive to inhibiting convection by lowering temperature and humidity. Subsequently, we investigate the impact of assimilating non-precipitation information to a real case on July 23, 2013, by performing a subsequent 9-hour forecast. The experiment that assimilates radar non-precipitation information improves the model's precipitation forecasts by showing an increase in the Fractional Skill Score (FSS) and a decrease in the False Alarm Ratio (FAR) compared to experiments in which do not assimilate non-precipitation information.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1273-1281
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• 1993

Estimation of daily and seasonal evaportranspiration is essential for water resource planning irrigation feasibility study, and real-time irrigation water management . This paper is to evaluate the applicability of neural networks to the estimation of evapotranspiration . A neural network was developed to forecast daily evapotranspiration of the rice crop. It is a three-layer network with input, hidden , and output layers. Back-propagation algorithm with delta learning rule was used to train the neural network. Training neural network wasconducted usign daily actural evapotranspiration of rice crop and daily climatic data such as mean temperature, sunshine hours, solar radiation, relative humidity , and pan evaporation . During the training, neural network parameters were calibrated. The trained network was applied to a set of field data not used in the training . The created response of the neural network was in good agreement with desired values. Evaluating the neural networ performance indicates that neural network may be applied to the estimation of evapotranspiration of the rice crop.

• Current Photovoltaic Research
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• v.4 no.2
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• pp.80-86
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• 2016

Since the last five years it has become a lot of solar power plants installed. However, by installing the large-scale solar power station it is not easy to predict the actual generation years. Because there are a variety of factors, such as changes daily solar radiation, temperature and humidity. If the power output can be measured accurately it predicts profits also we can measure efficiency for solar power plants precisely. Therefore, Prediction of power generation is forecast to be a useful research field. In this study, out discovering the factors that can improve the accuracy of the prediction of the photovoltaic power generation presents the means to apply them to the power generation amount prediction.

• Proceedings of the KSRS Conference
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• v.2
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• pp.660-663
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• 2006

Rainfall estimation is important to weather forecast, flood control, hydrological plan. The empirical and statistical methods by measured data(surface rain gauge, rainfall radar, Satellite) is commonly used for rainfall estimation. In this study, the rainfall intensity for East Asia region was estimated using the empirical relationship between SSM/I data of DMSP satellite and brightness temperature of GEOS-9(10.7${\mu}m$) with cloud types(ISCCP and MSG classification). And the empirical formula for rainfall estimation was produced by PMM (Probability Matching Method).