• 대기
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• 제28권3호
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• pp.273-289
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• 2018

This paper evaluates daily precipitation products from Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG), Tropical Rainfall Measuring Mission Multisatellite (TRMM) Precipitation Analysis (TMPA), and the Climate Prediction Center Morphing Method (CMORPH), validated against gauge observation over South Korea and gauge-based analysis data East Asia during one year from June 2014 to May 2015. It is found that the three products effectively capture the seasonal variation of mean precipitation with relatively good correlation from spring to fall. Among them, IMERG and TMPA show quite similar precipitation characteristics but overall underestimation is found from all precipitation products during winter compared with observation. IMERG shows reliably high performance in precipitation for all seasons, showing the most unbiased and accurate precipitation estimation. However, it is also noticed that IMERG reveals overestimated precipitation for heavier precipitation thresholds. This assessment work suggests the validity of the IMERG product for not only seasonal precipitation but also daily precipitation, which has the potential to be used as reference precipitation data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.378-381
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• 2007

Analyses of Tropical Rainfall Measuring Mission (TRMM) microwave radiometer (TMI) and precipitation radar (PR) data show that the rainfall inhomogeneity, represented by the coefficient of variation, decreases as rain rate increases at the low resolution (the footprint size of TMI 10 GHz channel). The rainfall inhomogeneity, however, is relatively constant for all rain rates at the high resolution (the footprint size of TMI 37 GHz channel). Consequently, radiometric signatures at lower spatial resolutions are characterized by larger dynamic range and smaller variability than those at higher spatial resolution. Based on the observed characteristics, this study develops a low-resolution (${\sim}40{\times}40$ km) rainfall retrieval algorithm utilizing realistic rainfall distributions in the a-priori databases. The purpose of the low-resolution rainfall algorithm is to make more reliable climatological rainfalls from various microwave sensors, including low-resolution radiometers.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• 대한원격탐사학회지
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• 제40권3호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.149-153
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• 2006

강우는 물과 에너지 순환에서 가장 중요한 역할을 한다. 이 연구에서는 원격탐사를 이용하여 추출한 강우자료의 불확실성 (uncertainty)이 수치수문모형에서 수문인자 (토양함수, 토양온도, 유출, 증발산, 열전도 등)를 모의할 때 공간 스케일의 영향을 검토해 보았다. 지상강우관측을 이용하여 보정된 WSR-88D (NEXRAD)에 의해 추출한 강우자료와 현장에서 측정된 기상자료를 입력 자료로 사용하여, 오프라인 CLM(Community Land Model) 수문모형을 세 가지의 다른 공간 스케일 $0.25^{\circ},\;0.5^{\circ}\;and\;1.0^{\circ}$에 대하여 수행하였다. 이어서 현장에서 측정된 기상자료는 고정시키고 동시공간에 해당하는 IR (Infrared) 밴드를 기반으로 하는 인공위성 강우자료로 대치시켜 같은 모형을 수행하여 비교 검토하였다. 이 연구에서는 물리적 이론을 기반으로 하는 CLM수문모형의 매개변수는 지표면-대기의 수문반응 (land-atmosphere interaction)을 적절하게 묘사하도록 정의되었다고 가정한다. 모형의 실험결과는 강우입력의 불확실성이 수문반응의 공간분포 결과에 어떻게 영향을 미치는지를 보여준다. 이 연구는 수문모형을 수행할 때 수문반응의 불확실성에 대한 정보를 제공해 주며, 결국은 기후 변화에 따른 수자원의 재분배를 이해하는데 이바지 할 것이다.

• 한국농공학회논문집
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• 제59권3호
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• 한국수자원학회논문집
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• 제39권10호
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• pp.823-832
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• 2006

강우는 물과 에너지 순환에서 가장 중요한 역할을 한다. 이 연구에서는 두개의 다른 원격탐사 센서를 이용하여 추출한 강우자료의 불확실성 (uncertainty)에 대하여 검토해 보았으며, 이에 의한 오차가 비선형 수치수문모형에서 수문인자(유출)를 모의할 때 어떻게 영향을 미치는가를 살펴보았다. 지상에서 관측된 강우 관측을 이용하여 WSR-88D (NEXRAD)에 의해 추출한 레이더 강우, 그리고 IR (Infrared) 밴드를 기반으로 하는 인공위성 강우관측을 비교 검토하였으며, 세 가지의 서로 다른 강우와 현장에서 측정된 기상자료를 입력 자료로 사용하여, 오프라인 CLM (Community Land Model) 수문모형으로 유출량을 모의하였다. 이 연구에서 물리적 이론을 기반으로 하는 CLM수문 모형의 매개변수는 지표면-대기의 수문반응 (land-atmosphere interaction)을 적절하게 묘사하도록 정의되었다고 가정한다. 다른 원격탐사 센서를 이용하여 추출한 강우자료는 시공간적으로 다른 양상을 보여 주며, 수치모형의 실험 결과는 강우입력의 불확실성이 수문반응의 결과에 어떻게 영향을 미치는지를 보여준다. 이 연구는 앞으로 우리나라에서 개발 및 활용가능성이 있는 레이더 강우와 인공위성 강우에 대한 사전 지식을 제공하고, 동시에 수치 수문모형을 수행할 때 수문반응의 불확실성에 대한 정보를 제공해 주며, 결국은 기후 변화에 따른 수자원의 재분배를 이해하는데 이바지할 것이다.

• 한국농공학회논문집
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• 제60권2호
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• pp.55-63
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• 2018

This study analyzed the applications of near real-time drought monitoring using satellite rainfall for the Korean Peninsula and un-gaged basins. We used AWS data of Yongdam-Dam, Hoengseong-Dam in Korea area, the meteorological station of Nakhon Rachasima, Pak chong for test-bed to evaluate the validation and the opportunity for un-gaged basins. In addition, we calculated EDI (Effective doought index) using the stations and co-located PERSIANN-CDR, TRMM (Tropical Rainfall Measurement Mission) TMPA (The TRMM Multisatellite Precipitation Analysis), GPM IMERG (the integrated Multi-satellitE Retrievals for GPM) rainfall data and compared the EDI-based station data with satellite data for applications of drought monitoring. The results showed that the correlation coefficient and the determination coefficient were 0.830 and 0.914 in Yongdam-dam, and 0.689 and 0.835 in Hoengseng-Dam respectively. Also, the correlation coefficient were 0.830, 0.914 from TRMM TMPA datasets and compasion with 0.660, 0.660 based on PERSIANN-CDR and TRMM data in nakhon and pakchong station. Our results were confirmed possibility of near real-time drought monitoring using EDI with daily satellite rainfall for un-gaged basins.

• 대기
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• 제32권4호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.250-250
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• 2016

인공위성을 이용한 강수관측은 전 지구적 규모에서 시공간적으로 균일한 강수정보를 지속적으로 제공할 수 있으며, 가뭄에 중요한 하나의 변수로서 가뭄정보를 제공할 수 있다는 장점이 있어 점차적으로 미계측지역 수문학적으로 활용성이 증대되고 있다. 그러나 인공위성 기반 강수관측자료는 지상관측 강우자료에 비해 시 공간해상도가 낮고, 관측 당시의 대기 상태, 관측기기, 시 공간적 대표성 문제 등에서 기인한 많은 불확실성을 포함하고 있다. 이러한 불확실성을 보완하기 위한 목적으로 미국 항공우주국 (National Aeronautics and Space Administration: NASA)는 GPM(Global Precipitation Measurement) 위성을 핵심위성으로 한 다중 위성자료를 이용하여 전지구적으로 30분 간격, 10 km 해상도의 GPM IMERG (Integrated Multi-satellitE Retrievals for GPM)를 생산 제공하고 있다. 본 연구에서는 다중 인공위성 추정 강수의 가뭄 활용성을 검토하기 위한 목적으로 GPM IMERG 위성 강우 자료(Early run, Late run, Final run)의 검증 및 평가를 수행하고자 하였으며, 각각의 자료들을 강수사례에 적용하여 10 km, 30분 해상도를 가지는 1.5km CAPPI (Constant Altitude Plan Position Indicator) 레이더 및 지상 강우자료와 비교 검증하였다.