• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.70-82
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• 2020

Recently, a lot of damages have been caused by urban flooding, and heavy rainfall that temporarily occur are the main causes of these phenomenons. The damages caused by urban flooding are identified as the change in the water balance in urban areas. To indirectly identify it, this research analyzed the change in the remote sensing indices on each land cover before and after heavy rainfall by utilizing daily precipitation data and multi-temporal Sentinel-2 satellite imagery. Cases of heavy rain advisory and warning were selected based on the daily precipitation data. And statistical fluctuation were compared by acquiring Sentinel-2 satellite images during the corresponding period and producing them as NDVI, NDWI and NDMI images about each land cover with a radius of 1,000 m based on the Seoul Weather Station. As a result of analyzing the maximum value, minimum value, mean and fluctuation of the pixels that were calculated in each remote sensing index image, there was no significant changes in the remote sensing indices in urban areas before and after heavy rainfall.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.447-459
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• 2022

This study estimated the grid-type precipitation quantile for the Korean Peninsula using PERSIANN-CCS-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record), a satellite based re-analysis precipitation data. The period considered is a total of 38 years from 1983 to 2020. The spatial resolution of the data is 0.04° and the temporal resolution is 3 hours. For the probability distribution, the Gumbel distribution which is generally used for frequency analysis was used, and the probability weighted moment method was applied to estimate parameters. The duration ranged from 3 hours to 144 hours, and the return period from 2 years to 500 years was considered. The results were compared and reviewed with the estimated precipitation quantile using precipitation data from the Automated Synoptic Observing System (ASOS) weather station. As a result, the parameter estimates of the Gumbel distribution from the PERSIANN-CCS-CDR showed a similar pattern to the results of the ASOS as the duration increased, and the estimates of precipitation quantiles showed a rather large difference when the duration was short. However, when the duration was 18 h or longer, the difference decreased to less than about 20%. In addition, the difference between results of the South and North Korea was examined, it was confirmed that the location parameters among parameters of the Gumbel distribution was markedly different. As the duration increased, the precipitation quantile in North Korea was relatively smaller than those in South Korea, and it was 84% of that of South Korea for a duration of 3 h, and 70-75% of that of South Korea for a duration of 144 h.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.55-62
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• 2006

Droughts have been an important factor in disaster management in Korea because she has been grouped into nations of lack of water. Satellite imagery can be applied to droughts monitoring because it can provide periodic data for large area for long time. This study aims to present a process to analyze droughts in large area using satellite imagery. We estimated evapotranspiration in large area using NDVI data acquired from satellite imagery. For satellite imagery, we dealt with MODIS data operated by NASA. The evapotranspiration estimated from satellite imagery was combined with precipitation data and potential evapotranspiration data to estimate water balances. Using water balances we could analyze droughts effectively in our object area. As the result of this study, we could increase the usability of satellite imagery, especially in droughts analysis.

• Atmosphere
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• v.15 no.1
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• pp.47-57
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• 2005

Extending the success of the Tropical Rainfall Measuring Mission (TRMM), the spaceborne measurement of precipitation by Global Precipitation Measurement (GPM) is initiated. The GPM consists of a core satellite which will have a dual-frequency precipitation radar (DPR) and a constellation of small satellites equipped with microwave radiometers. The GPM is inherently a global program. Responding to the GPM plan, many other nations are much interested in participating in the GPM team or simply utilizing GPM products aiming at the development of meteorological technology. Korea can fully function its role if Korea is selected as a CAL/VAL site for the GPM because Korea maintains a well-established dense rain gauge network (AWS), precipitation radars, and the Haenam super site for surface observation. In this feasibility study, the necessities of the GPM project in the context of academical and social backgrounds and associated international and domestic activities are investigated. And GPM-related core technologies and application areas are defined. As a result, it is found that GPM will represent a great opportunity for us because of its ability to provide not only much enhanced three-hourly global rain products but also very useful tools for the enhancement of weather forecasting capabilities, management of water resources, development and implementation of monitoring techniques for severe weather phenomena, agricultural managements and climate application. Furthermore, rain retrieval and CAL/VAL technologies obtained during the involvement in the international GPM project will serve as basic knowledges to run our own geostationary satellite program.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.131-140
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• 2018

Precipitation is a key variable to enhance the understanding of water cycle system and secure and manage the water resources efficiently. In this study, we evaluated the feasibility of GPM precipitation datasets through comparison with the 92 ASOS sites in South Korea during 2015. Additionally, three merging techniques (i.e., Geographical Differential Analysis, Geographical Ratio Analysis, Conditional Merging) were applied to improve accuracy of precipitation by fusing the advantages from point and satellite-based datasets. The results of this study are as follows. 1) GPM dataset indicated slightly overestimation with compared ASOS dataset, especially high uncertainties in summer season. 2) Validation of three merging techniques through jackniffe cross-validation showed that uncertainty were decreased as the spatial resolution increased. Especially, conditional merging showed the best performance among three methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.158-158
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• 2023

Characterizing the performance of precipitation (hereafter PRE) products in estimating the uncertainties in daily PRE in the era of global warming is of great value to the ecosystem's sustainability and human survival. This study intercompares the performance of different PRE products (gauge-based, satellite and reanalysis) sourced from the Frequent Rainfall Observations on GridS (FROGS) database over diverse climate zones in Africa and identifies regions where they depict minimal uncertainties in order to build optimal maps as a guide for different climate users. This is achieved by utilizing various techniques, including the triple collection (TC) approach, to assess the capabilities and limitations of different PRE products over nine climatic zones over the continent. For daily scale analysis, the uncertainties in light PRE (0.1 5mm/day) are prevalent over most regions in Africa during the study duration (2001-2016). Estimating the occurrence of extreme PRE events based on daily PRE 90th percentile suggests that extreme PRE is mainly detected over central Africa (CAF) region and some coastal regions of west Africa (WAF) where the majority of uncorrected satellite products show good agreement. The detection of PRE days and non-PRE days based on categorical statistics suggests that a perfect POD/FAR score is unattainable irrespective of the product type. Daily PRE uncertainties determined based on quantitative metrics show that consistent, satisfactory performance is demonstrated by the IMERG products (uncorrected), ARCv2, CHIRPSv2, 3B42v7.0 and PERSIANN_CDRv1r1 (corrected), and GPCC, CPC_v1.0, and REGEN_ALL (gauge) during the study period. The optimal maps that show the classification of products in regions where they depict reliable performance can be recommended for various usage for different stakeholders.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.330-330
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• 2022

우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

• Journal of the Korean earth science society
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• v.24 no.1
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• pp.22-29
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• 2003

Temporal and spatial variability of precipitation (P), evaporation (E), and moisture balance (P-E; precipitation minus evaporation) has been investigated over the tropical ocean during the period from January 1998 to July 2001. Our data were analyzed by the EOF method using the satellite P and E observations made by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and the Special Sensor Microwave/Imager (SSM/I). This analysis has been performed for two three-year periods as follow; The first period which includes the El Ni${\tilde{n}}$o in early 1998 ranges from January 1998 to December 2000, and the second period which includes the La Ni${\tilde{n}}$o events in the early 1999 and 2000 (without El Ni${\tilde{n}}$o) ranges from August 1998 to July 2001. The areas of maxima and high variability in the precipitation and in the P-E were displaced from the tropical western Pacific and the ITCZ during the La Ni${\tilde{n}}$o to the tropical middle Pacific during the El Ni${\tilde{n}}$o, consistent with those in previous P studies. Their variations near the Korean Peninsula seem to exhibit a weakly positive correlation with that in the tropical Pacific during the El Ni${\tilde{n}}$o. The evaporation, out of phase with the precipitation, was reduced in the tropical western Pacific due to humid condition in boreal summer, but intensified in the Kuroshio and Gulf currents due to windy condition in winter. The P-E variability was determined mainly by the precipitation of which the variability was more localized but higher by 2-3 times than that of evaporation. Except for the ITCZ (0-10$^{\circ}$N), evaporation was found to dominate precipitation by ${\sim}$2 mm/day over the tropical Pacific. Annual and seasonal variations of P, E, and P-E were discussed.

• Atmosphere
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• v.21 no.3
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• pp.257-271
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• 2011

The aim of this study is to examine weather modification by urbanization and human activities. The characteristics of the urban heat island (UHI) and precipitation in Seoul metropolitan area of Korea are investigated to demonstrate that cities can change or modify local and nearby weather and climate, and to confirm that cities can initiate convection, change the behavior of convective precipitation, and enhance downstream precipitation. The data used in this study are surface meteorological station data observed in Seoul and its nearby 5 cities for the period of 1960 to 2009, and 162 Automatic Weather System stations data observed in the Seoul metropolitan area from 1998 to 2009. Air temperature and precipitation amount tend to increase with time, and relative humidity decreases because of urbanization. Similar to previous studies for other cities, the average maximum UHI is weakest in summer and is strong in autumn and winter, and the maximum UHI intensity is more frequently observed in the nighttime than in the daytime, decreases with increasing wind speed, and is enhanced for clear skies. Relatively warm regions extend in the east-west direction and relatively cold regions are located near the northern and southern mountains inside Seoul. The satellite cities in the outskirts of Seoul have been rapidly built up in recent years, thus exhibiting increases in near-surface air temperature. The yearly precipitation amount during the last 50 years is increased with time but rainy days are decreased. The heavy rainfall events of more than $20mm\;hr^{-1}$ increases with time. The substantial changes observed in precipitation in Seoul seem to be linked with the accelerated increase in the urban sprawl in recent decades which in turn has induced an intensification of the UHI effect and enhanced downstream precipitation. We also found that the frequency of intense rain showers has increased in Seoul metropolitan area.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.269-274
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• 2024

High-quality precipitation data are crucial for various industries, including disaster prevention. In South Korea, long-term high-quality data are collected through numerous ground observation stations. However, data between these stations are reprocessed into a grid format using interpolation methods, which may not perfectly match actual precipitation. A prime example of real-time observational grid data globally is the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) from National Aeronautics and Space Administration (NASA), while in South Korea, ground radar data are more commonly used. GPM and ground radar data exhibit distinct differences due to their respective processing methods. This study aims to analyze the characteristics of GPM and Constant Altitude Plan Position Indicator(CAPPI),representative real-time grid data, by comparing them with ground-observed precipitation data. The study period spans from 2021 to 2022, focusing on hourly data from Automated Synoptic Observing System (ASOS) sites in South Korea. The GPM data tend to underestimate precipitation compared to ASOS data, while CAPPI shows errors in estimating low precipitation amounts. Through this comparative analysis, the study anticipates identifying key considerations for utilizing these data in various applied fields, such as recalculating design rainfall, thereby aiding researchers in improving prediction accuracy by using appropriate data.