Evaluation on penetration rate of cloud for incoming solar radiation using geostationary satellite data

Solar surface insolation (SSI) represents how much solar radiance reaches the Earth??s surface in a specified area and is an important parameter in various fields such as surface energy research, meteorology, and climate change. This study calculates insolation using Multi-functional Transport Satellite (MTSAT-1R) data with a simplified cloud factor over Northeast Asia. For SSI retrieval from the geostationary satellite data, the physical model of Kawamura is modified to improve insolation estimation by considering various atmospheric constituents, such as Rayleigh scattering, water vapor, ozone, aerosols, and clouds. For more accurate atmospheric parameterization, satellite-based atmospheric constituents are used instead of constant values when estimating insolation. Cloud effects are a key problem in insolation estimation because of their complicated optical characteristics and high temporal and spatial variation. The accuracy of insolation data from satellites depends on how well cloud attenuation as a function of geostationary channels and angle can be inferred. This study uses a simplified cloud factor that depends on the reflectance and solar zenith angle. Empirical criteria to select reference data for fitting to the ground station data are applied to suggest simplified cloud factor methods. Insolation estimated using the cloud factor is compared with results of the unmodified physical model and with observations by ground-based pyranometers located in the Korean peninsula. The modified model results show far better agreement with ground truth data compared to estimates using the conventional method under overcast conditions.     

Landslide susceptibility mapping using random forest and boosted tree models in Pyeong-Chang,Korea

Landslides susceptibility maps were constructed in the Pyeong-Chang area, Korea, using the Random Forest and Boosted Tree models. Landslide locations were randomly selected in a 50/50 ratio for training and validation of the models. Seventeen landslide-related factors were extracted and constructed in a spatial database. The relationships between the observed landslide locations and these factors were identified by using the two models. The models were used to generate a landslide susceptibility map and the importance of the factors was calculated. Finally, the landslide susceptibility maps were validated. Finally, landslide susceptibility maps were generated. For the Random Forest model, the validation accuracy in regression and classification algorithms showed 79.34 and 79.18%, respectively, and for the Boosted Tree model, these were 84.87 and 85.98%, respectively. The two models showed satisfactory accuracies, and the Boosted Tree model showed better results than the Random Forest model.     

Multisite campaign on the open cluster M67 – I. Observations and photometric reductions

We report on an ambitious multisite campaign aimed at detecting stellar variability, particularly solar-like oscillations, in the red giant stars in the open cluster M67 (NGC 2682). During the six-week observing run, which comprised 164 telescope nights, we used nine 0.6-m to 2.1-m class telescopes located around the world to obtain uninterrupted time series photometry. We outline here the data acquisition and reduction, with emphasis on the optimization of the signal-to-noise ratio of the low-amplitude (50–500 μmag) solar-like oscillations. This includes a new and efficient method for obtaining the linearity profile of the CCD response at ultrahigh precision (∼10 parts per million). The noise in the final time series is 0.50 mmag per minute integration for the best site, while the noise in the Fourier spectrum of all sites combined is 20 μmag. In addition to the red giant stars, this data set proves to be very valuable for studying high-amplitude variable stars such as eclipsing binaries, W UMa systems and δ Scuti stars.     

Changes and development plans in the mountain villages of South Korea: Comparison of the first and second national surveys

Owing to the geographic disadvantages of mountain villages, the social, cultural, and economic conditions of mountain villagers are inferior to those of urban dwellers in South Korea. Thus, in 1995, the The government of South Korea launched a mountain village development support program to promote agriculture and forestry, balance national land development, and preserve cultural heritage. The program was effectively implemented, improving the income, population size, and living conditions of villagers in addition to setting up a system for stable project implementation. However, concerns were raised about long-term development planning, the creation and marketing of specialty brands, facility management/operation, and follow-up support. The government conducted surveys of mountain villagers in 2003 and 2014, obtaining basic data to address these issues. This study evaluates the outcomes of these two surveys, suggesting areas requiring focused action, concentrating on village development projects, forest resource distribution and use, demographic trends, the economy, exchange with urban areas, green tourism, and master planning. We find that despite growth in the forest labor force, forest ownership is diminishing in terms of the number and scale of holdings. Consequently, it is necessary to commercialize forest resources, establish favorable settlement conditions, and expand government support for village-run projects. In addition, systematic forest management for older tree age classes would benefit the public and provide assets for future mountain village development. Our results are expected to provide baseline information for the establishment and efficient implementation of mountain village development policy.     

Hazard rate estimation of a mixture model with censored lifetimes

This paper is intended to compare the hazard rate from the Bayesian approach with the hazard rate from the maximum likelihood estimate (MLE) method. The MLE of a parameter is appropriate as long as there are sufficient data. For various reasons, however, sufficient data may not be available, which may make the result of the MLE method unreliable. In order to resolve the problem, it is necessary to rely on judgment about unknown parameters. This is done by adopting the Bayesian approach. The hazard rate of a mixture model can be inferred from a method called Bayesian estimation. For eliciting a prior distribution which can be used in deriving a Bayesian estimate, a computerized-simulation method is introduced. Finally, a numerical example is given to illustrate the potential benefits of the Bayesian approach.     

Web-based analytical tools for the exploration of spatial data

This paper deals with the extension of internet-based geographic information systems with functionality for exploratory spatial data analysis (esda). The specific focus is on methods to identify and visualize outliers in maps for rates or proportions. Three sets of methods are included: extreme value maps, smoothed rate maps and the Moran scatterplot. The implementation is carried out by means of a collection of Java classes to extend the Geotools open source mapping software toolkit. The web based spatial analysis tools are illustrated with applications to the study of homicide rates and cancer rates in U.S. counties.This research was supported in part by a number of grants from the US National Science Foundation: NSF Grant SBR-9410612, BCS-9978058, to the Center for Spatially Integrated Social Science (csiss), and a grant from the National Consortium on Violence Research (ncovr is supported under grant SBR-9513040 from the National Science Foundation). In addition, support was provided by grant RO1 CA 95949-01 from the National Cancer Institute. Special thanks to Dr. Eugene J. Lengerich of the Pennsylvania State Cancer Institute for providing the data on colon cancer diagnoses.     

Comparison of satellite measurements of the low-latitude nighttime upper ionosphere with IRI

In this paper, we report the results of our comparison study between satellite measurements and the International Reference Ionosphere (IRI) model on the seasonal and longitudinal changes of the low-latitude nighttime topside ionosphere during the period of solar maximum from June 2000 to July 2001. Satellite measurements were made by KOMPSAT-1 and DMSP F15 at 685 km altitude and 840 km altitude, respectively. The results show that the IRI2001 model gives reasonable density estimations for the summer hemisphere and the March equinox at both altitudes. However, the observed wintertime densities are smaller than the predictions of the IRI2001 model, especially at a higher (840 km) altitude, manifesting strong hemispheric asymmetries. The observed electron temperatures generally reside between the two estimations of IRI2001, one based on the Aeros–ISIS data and the other based on Intercosmos, and the latter estimation better represents the observations. With more or less monotonic increase with latitude, the temperature profiles of the IRI2001 model do not predict the enhancement seen around 15° magnetic latitude of the winter hemisphere. Longitudinal variation, probably caused by the zonal winds, is seen in all seasons at both altitudes, while the IRI2001 model does not show a large variation. The observed density and temperature show significant changes according to the F10.7 values in the whole low-latitude region from 40°S to 40°N geomagnetic latitude. The effect is manifested as increases in the density and temperature, but not in the hemispheric asymmetry or in the longitudinal variation.     

Large-scale rainfall–runoff–inundation modeling for upper Citarum River watershed,Indonesia

The Citarum River is one of the strategic rivers in West Java, Indonesia. Its total watershed area is approximately 1800 km². Almost every year, the overflow from the Citarum River causes the inundation of most of the upper Citarum River watershed. To prevent and mitigate flood damage, it is necessary to understand the flooding characteristics. The region, however, suffers from a lack of observational data. Therefore, to analyze the inundation caused by flooding in the upper Citarum River watershed, a rainfall–runoff–inundation (RRI) model was employed. It used the following multiple satellite-derived datasets as input data as well as for model verification: Global Satellite Mapping of Precipitation, Hydrological data and maps based on Shuttle elevation Derivatives at multiple scales, Global Mosaics of the standard MODIS land cover type data product, and Landsat 7 satellite images. Parameter calibration was performed using a Monte Carlo simulation. The simulation was performed for February 2010. The results of this study show that the RRI model identifies inundation areas in large-scale river watersheds more effectively when using multiple satellite-derived datasets compared with the observed inundation map obtained from JICA in 2010 and Landsat 7 images. The model results can be improved if high-quality observed rainfall data, topographic data, and river cross-sectional data are available.     

Subspace system identification of support‐excited structures—part I: theory and black‐box system identification

This paper reviews the theoretical principles of subspace system identification as applied to the problem of estimating black‐box state‐space models of support‐excited structures (e.g., structures exposed to earthquakes). The work distinguishes itself from past studies by providing readers with a powerful geometric interpretation of subspace operations that relates directly to theoretical structural dynamics. To validate the performance of subspace system identification, a series of experiments are conducted on a multistory steel frame structure exposed to moderate seismic ground motions; structural response data is used off‐line to estimate black‐box state‐space models. Ground motions and structural response measurements are used by the subspace system identification method to derive a complete input–output state‐space model of the steel frame system. The modal parameters of the structure are extracted from the estimated input–output state‐space model. With the use of only structural response data, output‐only state‐space models of the system are also estimated by subspace system identification. The paper concludes with a comparison study of the modal parameters extracted from the input–output and output‐only state‐space models in order to quantify the uncertainties present in modal parameters extracted from output‐only models. Copyright © 2012 John Wiley & Sons, Ltd.