Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI)

This paper describes an atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI) and its early phase evaluation. This algorithm was implemented in GOCI Data Processing System (GDPS) version 1.1. The algorithm is based on the standard SeaWiFS method, which accounts for multiple scattering effects and partially updated in terms of turbid case-2 water correction, optimized aerosol models, and solar angle correction per slot. For turbid water correction, we used a regional empirical relationship between water reflectance at the red (660 nm) and near infrared bands (745 nm and 865 nm). The relationship was derived from turbid pixels in satellite images after atmospheric correction, and processed using aerosol properties derived for neighboring non-turbid waters. For validation of the GOCI atmospheric correction, we compared our results with in situ measurements of normalized water leaving radiance (nL _w ) spectra that were obtained during several cruises in 2011 around Korean peninsula. The match up showed an acceptable result with mean ratio of the GOCI to in situ nL _w (??), 1.17, 1.24, 1.26, 1.15, 0.86 and 0.99 at 412 nm, 443 nm, 490 nm, 555 nm, 660 nm and 680 nm, respectively. It is speculated that part of the deviation arose from a lack of vicarious calibration and uncertainties in the above water nLw measurements.     

Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS

Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.     

Magnetospheric convection at a low level power ϵ

It is demonstrated that the magnetospheric convection becomes evident in terms of the AE index only when the power ? of the solar wind-magnetosphere dynamo becomes greater than ～ 10¹⁸ erg s^?1 or a slightly lower value. An enhanced conductivity is a crucial factor for the magnetospheric convection to manifest even in a low-level increase of the AE index of ～ 50–100 γ.     

On the variation of frequency-based rainfall amounts: a case study for evaluating recent extreme rainfalls in Korea

Extreme rainfall events recently occurring in Korea have been shown to change frequency-based rainfall amounts quite significantly. Regardless of the reason for these extremes, the general concern of most hydrologists is how to handle these events for practical applications in Hydrology. Our study aim is to evaluate these extremes with their effect on frequency-based rainfall amounts, especially if they can be assumed to be within normal levels. As there is no commonly accepted methodology to be applied to this kind of study, we follow simplified steps such as: (1) estimation of the climatological variance of frequency-based rainfall amounts, (2) estimation of confidence intervals of frequency-based rainfall amounts (lower and upper bounds for the 5 and 1% significance levels estimated using the climatological variance), and (3) evaluation of the effect of extra rainfall events on the frequency-based rainfall amounts. Twelve stations on the Korean peninsula are selected as they have relatively longer data length. The annual maximum rainfall data collected from 1954 to 1998 are used. From this study we concluded that (1) at least 30 years of data length should be used for the frequency analysis in order to assure the stability of the variance of frequency-based rainfall amounts, (2) the climatological variances estimated all range from 5 to 8% of the frequency-based rainfall amounts, and (3) even though the frequency-based rainfall amount seems to become extreme with seemingly abnormal events, it still remains under its upper bound for the 5 or 1% significance levels estimated using the climatological variance, as well as it decays exponentially to the normal level as extra events are added. Thus, we conclude that we do not need to panic over seemingly abnormal events occurring so far, but just need to consider the variability inherent in frequency-based rainfall amounts.     

Application of an artificial neural network for a direct estimation of atmospheric instability from a next-generation imager

Atmospheric instability information derived from satellites plays an important role in short-term weather forecasting,especially the forecasting of severe convective storms. For the next generation of weather satellites for Korea's multi-purpose geostationary satellite program, a new imaging instrument has been developed. Although this imaging instrument is not designed to perform full sounding missions and its capability is limited, its multi-spectral infrared channels provide information on vertical sounding. To take full advantage of the observation data from the much improved spatiotemporal resolution of the imager, the feasibility of an artificial neural network approach for the derivation of the atmospheric instability is investigated.The multi-layer perceptron model with a feed-forward and back-propagation training algorithm shows quite a sensitive response to the selection of the training dataset and model architecture. Through an extensive performance test with a carefully selected training dataset of 7197 independent profiles, the model architectures are selected to be 12, 5000, and 0.3 for the number of hidden nodes, number of epochs, and learning rate, respectively. The selected model gives a mean absolute error,RMSE, and correlation coefficient of 330 J kg~(-1), 420 J kg~(-1), and 0.9, respectively. The feasibility is further demonstrated via application of the model to real observation data from a similar instrument that has comparable observation channels with the planned imager.     

Line-by-line radiative transfer model for infrared spectrum of AERI

Infrared radiance spectra measured in space or on the ground have been used for many applications, such as the retrieval of atmospheric temperature and humidity profiles. The Korean Meteorological Administration (KMA) recently installed an Atmospheric Emitted Radiance Interferometer (AERI) system at the Korea Global Atmosphere Watch Center (36°32??N, 125°19??E) in Anmyondo to measure the downward radiance spectra on the ground. For further utilization of such interferometeric radiance measurements, an accurate line-by-line radiative transfer model is required. This study introduces a line-by-line radiative transfer model developed at Kyungpook National University (KNU_LBL) and presents comparisons of spectra simulated using the KNU_LBL model and measured by the AERI system, that is installed inside a secure container. When compared with the Atmospheric and Environmental Research (AER) radiative transfer codes, the KNU_LBL model provides nearly identical spectra for various model atmospheres. The simulated spectra are also in good agreement with the AERI spectra for clear sky conditions, and a further improvement is made when taking into account of the emissions and absorption by CO₂ and H₂O for the light path inside the container, even though the path is short.     

Assessing drought threats to agricultural water supplies under climate change by combining the SWAT and MODSIM models for the Geum River basin,South Korea

ABSTRACT

The impacts of future climate change on the agricultural water supply capacities of irrigation facilities in the Geum River basin (9645.5 km²) of South Korea were investigated using an integrated modeling framework that included a water balance network model (MODSIM) and a watershed-scale hydrologic model (Soil and Water Assessment Tool, SWAT). The discharges and baseflows from upland drainage areas were estimated using SWAT, and the predicted flow was used to feed agricultural reservoirs and multipurpose dams in subwatersheds. Using a split sampling method, we calibrated the daily streamflows and dam inflows at three locations using data from 6 years, including 3 years of calibration data (2005–2007) followed by 3 years of validation data (2008–2010). In the MODSIM model, the entire basin was divided into 14 subwatersheds in which various agricultural irrigation facilities such as agricultural reservoirs, pumping stations, diversions, culverts and groundwater wells were defined as a network of hydraulic structures within each subwatershed. These hydraulic networks between subwatersheds were inter-connected to allow watershed-scale analysis and were further connected to municipal and industrial water supplies under various hydrologic conditions. Projected climate data from the HadGEM3-RA RCP 4.5 and 8.5 scenarios for the period of 2006–2099 were imported to SWAT to calculate the water yield, and the output was transferred to MODSIM in the form of time-series boundary conditions. The maximum shortage rate of agricultural water was estimated as 38.2% for the 2040s and 2080s under the RCP 4.5 scenario but was lower under the RCP 8.5 scenario (21.3% in the 2040s and 22.1% in the 2080s). Under the RCP 4.5 scenario, the projected shortage rate was higher than that during the measured baseline period (1982–2011) of 25.6% and the RCP historical period (1982–2005) of 30.1%. The future elevated drought levels are primarily attributed to the increasingly concentrated rainfall distribution throughout the year under a monsoonal climate, as projected by the IPCC climate scenarios.

EDITOR Z.W. Kundzewicz; ASSOCIATE EDITOR not assigned     

Dynamic characteristics of monthly rainfall in the Korean Peninsula under climate change

Global climate change is one of the most serious issues we are facing today. While its exact impacts on our water resources are hard to predict, there is a general consensus among scientists that it will result in more frequent and more severe hydrologic extremes (e.g. floods, droughts). Since rainfall is the primary input for hydrologic and water resource studies, assessment of the effects of climate change on rainfall is essential for devising proper short-term emergency measures as well as long-term management strategies. This is particularly the case for a region like the Korean Peninsula, which is susceptible to both floods (because of its mountainous terrain and frequent intense rainfalls during the short rainy season) and droughts (because of its smaller area, long non-rainy season, and lack of storage facilities). In view of this, an attempt is made in the present study to investigate the potential impacts of climate change on rainfall in the Korean Peninsula. More specifically, the dynamics of ‘present rainfall’ and ‘future rainfall’ at the Seoul meteorological station in the Han River basin are examined and compared; monthly scale is considered in both cases. As for ‘present rainfall,’ two different data sets are used: (1) observed rainfall for the period 1971–1999; and (2) rainfall for the period 1951–1999 obtained through downscaling of coarse-scale climate outputs produced by the Bjerknes Center for Climate Research-Bergen Climate Model Version 2 (BCCR-BCM2.0) climate model with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) 20th Century Climate in Coupled Models (20C3M) scenario. The ‘future rainfall’ (2000–2099) is obtained through downscaling of climate outputs projected by the BCCR-BCM2.0 with the A2 emission scenario. For downscaling of coarse-scale climate outputs to basin-scale rainfall, a K-nearest neighbor (K-NN) technique is used. Examination of the nature of rainfall dynamics is made through application of four methods: autocorrelation function, phase space reconstruction, correlation dimension, and close returns plot. The results are somewhat mixed, depending upon the method, as to whether the rainfall dynamics are chaotic or stochastic; however, the dynamics of the future rainfall seem more on the chaotic side than on the stochastic side, and more so when compared to that of the present rainfall.     

Uncertainties in limits on TeV-gravity from neutrino-induced showers

In models with TeV-scale gravity, ultrahigh energy cosmic rays can generate microscopic black holes in the collision with atmospheric and terrestrial nuclei. It has been proposed that stringent bounds on TeV-scale gravity can be obtained from the absence of neutrino cosmic ray showers mediated by black holes. However, uncertainties in the cross section of black hole formation and, most importantly, large uncertainties in the neutrino flux affects these bounds. As long as the cosmic neutrino flux remains unknown, the non-observation of neutrino induced showers implies less stringent limits than present collider limits.