• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.1101-1117
• /
• 2018

The clear sky radiance (CSR) is one of the baseline products of the Himawari-8 which was launched on October, 2014. The CSR contributes to numerical weather prediction (NWP) accuracy through the data assimilation; especially water vapor channel CSR has good impact on the forecast in high level atmosphere. The focus of this study is the quality analysis of the CSR of the Himawari-8 geostationary satellite. We used the operational CSR (or clear sky brightness temperature) products in JMA (Japan Meteorological Agency) as observation data; for a background field, we employed the CSR simulated using the Radiative Transfer for TOVS (RTTOV) with the atmospheric state from the global model of KMA (Korea Meteorological Administration). We investigated data characteristics and analyzed observation minus background statistics of each channel with respect to regional and seasonal variability. Overall results for the analysis period showed that the water vapor channels (6.2, 6.9, and $7.3{\mu}m$) had a positive mean bias where as the window channels(10.4, 11.2, and $12.4{\mu}m$) had a negative mean bias. The magnitude of biases and Uncertainty result varied with the regional and the seasonal conditions, thus these should be taken into account when using CSR data. This study is helpful for the pre-processing of Himawari-8/Advanced Himawari Imager (AHI) CSR data assimilation. Furthermore, this study also can contribute to preparing for the utilization of products from the Geo-Kompsat-2A (GK-2A), which will be launched in 2018 by the National Meteorological Satellite Center (NMSC) of KMA.

• Journal of Korea Water Resources Association
• /
• v.36 no.3 s.134
• /
• pp.495-505
• /
• 2003

Convective weather systems such as organized mesoscale convective systems (Mesoscale Convective Complex, MCC and Convective Cloud Clusters, CCC) and much weaker Disorganized Short-lived Convection (DSC) in the region of India and Nepal were analyzed using the Meteosat-5 IR imagery. The diurnal march and propagation of patterns of convective activity in the Himalayas and Northern Indian subcontinent were examined. Results indicate that infrared satellite images of Northern India and along the southern flank of the Himalayas reveal a strong presence of convective weather systems during the 1999 and 2000 monsoons, especially in the afternoon and during the night. The typical MCCs have life-times of about 11 hours, and areal extent about $300,000km^2$. Although the core of MCC activity remains generally away from the Middle Himalayan range, the occurrence of heavy precipitation events in this region can be directly linked to MCCs that venture into the Lesser Himalayan region and remain within the region bounded by $25^{\circ}-30^{\circ}N$. One principal feature in the spatial organization of convection is the dichotomy between the Tibetan Plateau and the Northern Indian Plains: CCCs and DSCs begin in the Tibetan Plateau in the mid-afternoon into the evening; while they are most active in the mid-night and early morning in the Gangetic Plains and along the southern facing flanks of the Himalayas. Furthermore, these data are consistent with the daily cycle of rainfall documented for a network of 20 hydrometeorological stations in Central Nepal, which show strong nocturnal peaks of intense rainfall consistent with the close presence of Convective Weather Systems (CWSs) in the Gangetic Plains (Barros et al. 2000).

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.39 no.9
• /
• pp.735-742
• /
• 2015

In this paper, we compare and verify the prediction accuracy and feasibility for wind resources on a wind farm using the Weather Research and Forecasting (WRF) model, which is a numerical weather-prediction model. This model is not only able to simulate local weather phenomena, but also does not require automatic weather station (AWS), satellite, or meteorological mast data. To verify the feasibility of WRF to predict the wind resources required from a wind farm pre-feasibility study, we compare and verify measured wind data and the results predicted by WAsP. To do this, we use the Pyeongdae and Udo sites, which are located on the northeastern part of Jeju island. Together with the measured data, we use the results of annual and monthly mean wind speed, the Weibull distribution, the annual energy production (AEP), and a wind rose. The WRF results are shown to have a higher accuracy than the WAsP results. We therefore confirmed that WRF wind resources can be used in wind farm pre-feasibility studies.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05a
• /
• pp.43-50
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of Astronomy and Space Sciences
• /
• v.21 no.4
• /
• pp.441-452
• /
• 2004

Nowcast and forecast based on realtime data are quite essential for space weather monitoring. We have developed the web pages (http://sun.kao.re.kr) of the KAO Space Weather Monitoring system by using ION (IDL on the Net). They display latest solar and geomagnetic data, and present their expected effects on satellite, communications and ground power system. In addition, daily NOAA/SEC prediction reports on the probability of solar X-ray flares, proton events and geomagnetic storms are provided. To predict the arrival times of interplanetary shocks and CMEs, two different types of prediction models are also implemented. A work is in progress to develop web-based database of several solar and geomagnetic activities. These data are automatically downloaded to our data server in every minute, or every day using IDL and FTP programs. In this paper, we will introduce more details on the development of the KAO Space Weather Monitoring system.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.309-312
• /
• 2008

The advent of high resolution products of surface wind and temperature derived by satellite data has permitted us to investigate ocean and atmosphere interaction studies in detail. Especially the Kuroshio extension region of the western North Pacific is considered to be a key area for such studies. We have constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (Qscat/SeaWinds), available as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO). Using new data based on improved algorithm which have been recently delivered, we are reconstructing gridded product with higher spatial resolution. Intercomparison of this product with the previous one reveals that there are some discrepancies between them in short-period and high wind-speed ranges especially in the westerly wind region. The products are validated by not only comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON in the tropical Pacific and the Kuroshio Extension Observation (KEO) buoys, but also intercomparison with numerical weather prediction model (NWPM) products (the NRA-1 and 2). Our products have much smaller mean difference in the study areas than the NWPM ones, meaning higher reliability compared with the NWPM products. Using the high resolution products together with sea surface temperature (SST) data, we examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region. It is suggested that the spatial relation between the wind speed and SST depends upon, more or less, the surrounding oceanic condition.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.289-292
• /
• 2008

Recently, several satellite data analyses projects and numerical weather prediction (NWP) reanalysis projects have produced the ocean surface Latent Heat Flux (LHF) data sets in the global coverage. Comparisons of these LHF data sets showed substantial discrepancies in the LHF values. Recently, the increase of LHF in during 1970s-1990s over the global ocean is shown by the LHF data that have been developed at the Objective Analyzed Air-Sea Fluxes (OAFlux) project. It is interesting to investigate the existence of the increase of LHF over a global ocean in the other LHF products. It is interesting to investigate the existence of the increase of LHF over a global ocean in the other LHF products. In this study, we assessed the consistencies and discrepancies of the inter-annual variability and decadal trend for the period 1988-2005 among six LHF products ((J-OFURO2, HOAPS3, IFREMER, NCEP1,2 and OAFlux) over the global ocean. As results, all LHF products showed a positive trend. In particular, the positive trend in satellite-based data analyses (J-OFURO2, HOAPS3, IFREMER) is larger than that in reanalysis products (NCEP1/2). Also, the consistencies and discrepancies are shown on the spatial patterns of the LHF trends across the six data sets. The positive trend of LHF is remarkable in the regions of western boundary currents such as the Kuroshio and the Gulf Stream in all LHF data sets. But, the discrepancies are shown on the spatial patterns of the LHF trends in tropics and subtropics. These discrepancies are primarily caused by the differences of the input meteorological state variables, particularly for the air specific humidity, used to calculate LHF.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.32A no.3
• /
• pp.1-9
• /
• 1995

In the B-ISDN using satellite between geo-satellites and earth stations, the laser having high security and broad band width has to be used as a carrier for transmitting massive information of visual, vocal, and high rate data. In this paper, by computer simulation we analyzed the number of optical detector array of optical satellite communication downlink in case of using channel coding and no channel coding for BISDN between geo-satelites and earth stations under clear weather condition. It was supposed that 1 watt semiconductor laser was used and as modulation method, the binary FSK was used. The data rate of 10Gbps was used for B-ISDN. Also, hardly affected by atmospheric absorption 1.55$\mu$m wave-length was used to reduce influence of dispersion and chirp generated at a high speed transmission. We analyzed the received power, SNR and BER. The number of optical detector array was determined to satisfy for the BER less than 10$^{-7}$. Also, we ananlyzed the possibility of reducting the number of optical detector array in case of using channel coding. the number of optical detector array is one in the region where the elevation nangle is between 38$^{\circ}$ and 90$^{\circ}$ and two where the elevation angle is between 33$^{\circ}$ and 37$^{\circ}$ and three where the elevation angle is between 30$^{\circ}$ and 32$^{\circ}$ and increases per one as the elevation angle decreases per 1.deg.. So in the region where the elevation angle is 25$^{\circ}$, the number of optical detector arrays is eight. In case of using channel coding, the number of optical detector arrays decreases to five in the region where the elevation angle is 25$^{\circ}$. Therefore, we remaark the advantage of the channelcoding to decrease the size of received antenna and the number ob optical detector arrays.

• Journal of Environmental Science International
• /
• v.19 no.3
• /
• pp.281-293
• /
• 2010

The present study explores time and spatial thermal environment for Daegu, which is a city built on a basin area, according to varying land cover conditions of the earth's surface by analyzing data derived from meteorological observation and satellite images. The study has classified land use by utilizing MODIS satellite images and analyzed land surface temperature. Also, by using data acquired from automatic weather system, the study has evaluated the effects of atmospheric heating caused by city pavements by analyzing the sensible heat flux between the city's land surface and the atmosphere. The results are as follows. 1) Classification of land use in the Daegu area shows 46.64% of urban and built-up area, 1.39% of watersides, 35.19% of forest, 11.43% of crops, and 5.37% grasslands. 2) During the weekdays throughout the year, the land surface temperature was high for Dalseogu, Bukgu, and Seogu regions where industrial complexes could be found. Comparatively, lower temperature could be observed in the woodlands. 3) While the land surface temperature displayed the effects of pushing air upwards during the weekdays in urban areas, the reverse was true for forest regions. During the night, the temperature did not exert any significant influence on air movement.

• Journal of the korean society of oceanography
• /
• v.38 no.4
• /
• pp.173-184
• /
• 2003

Major differences between wind speeds from atmospheric pressure maps (Na wind) and near­surface wind speeds derived from satellite scatterometer (NSCAT) observations over the East (Japan) Sea have been examined. The root­mean­square errors of Na wind and NSCAT wind speeds collocated with Japanese Meteorological Agency (JMA) buoy winds are about $3.84\;ms^{-1}\;and\;1.53\;ms^{-1}$, respectively. Time series of NSCAT wind speeds showed a high coherency of 0.92 with the real buoy measurements and contained higher spectral energy at low frequencies (>3 days) than the Na wind. The magnitudes of monthly Na winds are lower than NSCAT winds by up to 45%, particularly in September 1996. The spatial structures between the two are mostly coherent on basin­wide large scales； however, significant differences and energy loss are found on a spatial scale of less than 100 km. This was evidenced by the temporal EOFs (Empirical Orthogonal Functions) of the two wind speed data sets and by their two­dimensional spectra. Since the Na wind was based on the atmospheric pressures on the weather map, it overlooked small­scale features of less than 100 km. The center of the cold­air outbreak through Vladivostok, expressed by the Na wind in January 1997, was shifted towards the North Korean coast when compared with that of the NSCAT wind, whereas NSCAT winds revealed its temporal evolution as well as spatial distribution.