• Ocean and Polar Research
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• v.23 no.2
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• pp.189-194
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• 2001

A practical algorithm for prediction of the sea surface temperatures (SST)from the satellite remote sensing data is presented in this paper. The fluctuations of SST consist of deterministic normals and stochastic anomalies. Due to large thermal inertia of sea water, the SST anomalies can be modelled by autoregressive or Markov process, and its near future values can be predicted provided the recent values of SST are available. The actual SST is predicted by superposing the pre-known SST normals and the predicted SST anomalies. We applied this prediction algorithm to the NOAA AVHRR weekly SST data for 18 years (1981-1998) in the seas adjacent to Korea (115-$145^{\circ}E$, 20-$55^{\circ}N$). The algorithm is applicable not only for prediction of SST in near future but also for nowcast of SST in the cloud covered regions.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.49-57
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• 1998

CO2 transfer velocity is one of the key parameters for CO2 flux estimation at air - sea interface. However, current studies show that significant inconsistency still exists in its estimation when using different models and remotely sensed data sets, which acts as one of the main uncertainties involved in the computation of CO2 exchange coefficient between air - sea interface. In this study, wind data collected from SSM/I and scatterometer onboard ERS-1, in conjunction with operational NOAA/AVHRR, are applied to different models for calculating CO2 exchange coefficient in the world ocean. Their interrelationship and discrepancies inherent with different models and satellite data are analyzed. Finally, the seasonal and inter-annual variation of CO2 exchanges coefficient for different ocean basins are presented and discussed.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.43-48
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• 2001

Many applications in the areas of agricultural, hydrological and environmental resource management require data over very large areas and with a high imaging frequency - monitoring crop growth, water stress, seasonal wetland flooding and natural vegetation development. This precludes the use of fine resolution data (Landsat, Spot) on the grounds of cost, accessibility and low imaging frequency. Meteorological satellites have the potential to fill this need, given their very wide spatial coverage, and high repeat imaging. The Remote Sensing Unit (RSU) at the Zambia Meteorological Department routinely receives, processes and archives imagery from both Meteosat and NOAA AVHRR satellites. Here I wish to present some examples of applications of these data sets that arise from the RSU work - relationships between rainfall and vegetation development as assessed by satellite, derived information and seasonal patterns of flooding in the Barotse floodplain and the Kafue flats. I also wish to outline ways in which a more widespread use of this data by the Zambian institutions canbe achieved.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.341-349
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• 2003

The so-called B-method, a simplified surface energy budget, permits calculation of daily actual evapotranspiration (ET) using remotely sensed data, such as NOAA-AVHRR. Even if the use of satellite data allows estimation of the albedo and surface temperature, this model requires meteorological data measured at ground-level to obtain the other inputs. In addition, a difficulty may be occurred by the difference of temporal scales between the net radiation in daily scale and instantaneous measurement at midday of the surface and air temperatures because the data covered whole day are necessary to obtain accumulated daily net radiation. In order to solve these problems, this study attempted a modification of B-method through an extension of hourly ET value calculated using a complete instantaneous inputs. The estimation of the daily apparent ET from newly proposed system showed a root mean square error of 0.26 mm/day as compared the output obtained from the classical model. It is evident that this may offer more rapid estimation and reduced data volume.

• Journal of Astronomy and Space Sciences
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• v.11 no.1
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• pp.53-70
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• 1994

The Korean sounding rockets(KSR420S-1, -2) equipped with ozone detectors have b3en launched at An-heung, Chungchungnam-do, on June 4 and September 1, 1993, respectively. The ozone detector is used to measure the attenuation of solar UV radiation for various frequency bands in the stratosphere, to obtain vertical profiles of the ozone number density in the stratosphere. They confirm that the maximum ozone densities occur near 25 km, which is quite consistent with the mean value in the mid-latitude region. Our results from KSR420S-1 and -2 are compared with the other observation data from the Dobson spectrophotometer at Yonsei Univ., the LIDAR at Kyunghee Univ., the SBUV from Nimbus satellite, and the TOVS from NOAA satellite, which were performed simultaneously with the sounding rocket experiments.

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.47-54
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• 2000

We compared the satellite observed temperature with the radiosonde observed temperature in the Korean Peninsula. The radiosonde observed data were obtained from four upper air observation stations in the Korean Peninsula from 1981 to 1998, and were compared with the satellite observed data of the channel-2 and channel-4 of microwave sounding unit(MSU) on board NOAA series of polar-orbiting satellites. The radiosonde data were reconstructed from radiosonde T$_b$ using MSU weighting function. The monthly climatology shows radiosonde T$_{b2}$ is higher than MSU T$_{b2}$ in summer. The correlation between MSU T$_{b2}$ and radiosonde T$_{b2}$ is 0.72-0.76 and 0.73-0.81 between MSU T$_{b4}$ and radiosonde T$_{b4}$. The T$_{b2}$ show a positive trend and the T$_{b4}$ has a negative trend during the 18 years.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.45-59
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• 2009

This research presents the effect of Asian dust on the derived sea surface temperature (SST) from measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To analyze the effect, A VHRR infrared brightness temperature (TB) is estimated from simulated radiance calculated from radiative transfer model on various atmospheric conditions. Vertical profiles of temperature, pressure, and humidity from radiosonde observation are used to build up the East Asian atmospheric conditions in spring. Aerosol optical thickness (AOT) and size distribution are derived from skyradiation measurements to be used as inputs to the radiative transfer model. The simulation results show that single channel TB at window region is depressed under the Asian dust condition. The magnitude of depression is about 2K at nadir under moderate aerosol loading, but the magnitude reaches up to 4K at slant path. The dual channel difference (DCD) in spilt window region is also reduced under the Asian dust condition, but the reduction of DCD is much smaller than that shown in single channel TB simulation. Owing to the depression of TB, SST has cold bias. In addition, the effect of AOT on SST is amplified at large satellite zenith angle (SZA), resulting in high variance in derived SSTs. The SST depression due to the presence of Asian dust can be expressed as a linear function of AOT and SZA. On the basis of this relationship, the effect of Asian dust on the SST retrieval from the conventional daytime multi-channel SST algorithm can be derived as a function of AOT and SZA.

• Journal of the Korean GEO-environmental Society
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• v.9 no.6
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• pp.43-51
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• 2008

This study is to evaluate the NPP (Net Primary Production) distribution in the Geum River basin from NOAA/AVHRR satellite imagery data. It is supposed that the natural vegetation condition and the NPP has the linear relationship. The NPP from natural vegetation increases proportional to the annual net radiation (Rn), where radiative dryness index (RDI) is a proportional constant connecting net radiation to NPP. Normalized Difference Vegetation Index (NDVI) is used for monitoring vegetation change, and iNDVI (integrated NDVI) for annual analysis. The iNDVI has a close relation to Rn and NPP, which can be used effectively for estimating NPP distribution of where the meteorological data is unavailable. The purpose of this study is to propose a simple method to get NPP in the Geum river basin.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.71-81
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• 2007

One of the most important hydrologic components is evapotranspiration. It is a process by which water is evaporated from moist land surfaces and transpired into atmosphere by plants. There are many methods of estimating evapotranspiration rate and its potential such as the methods of soil-moisture sampling, lysimeter measurements, water balance, energy balance, groundwater fluctuations and evapotranspiration. But it is very difficult to estimate evapotranspiration in terms of regional discrete characteristics of topography and/or vegetation. The evapotranspiration is strongly affected by ground covering vegetation, and the degree of vegetation growth. In order to grasp vegetation condition over a vast study area, NDVI (Normalized Difference Vegetation Indices) calculated from the data obtained from NOAA/AVHRR were utilized. Through multi-regression analysis, we developed a model equation to estimate the evapotranspiration using NDVIs and temperature data.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.3
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• pp.20-30
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• 2000

Average annual NDVI values from the NOAA/NASA Pathfinder AVHRR Land Data Sets from 1982 to 1994 showed comprehensive systematic displacement patterns in Asia. Inter-annual growing season data, however, did not show such systematic patterns. The most likely cause for the abrupt displacements, which appear especially in 1982, 1989 and 1990, may be changes in satellite sensors, although global warming, El Ni$\tilde{n}$o-Southern Oscillation events, changes in processing algorithms, and changes in land-use patterns in various parts of Asia may also play some role. The results suggest that researchers must be extremely careful in their inter-annual global change research, since direct use of the raw data could cause unexpected results. Growing-season NDVI shows decreases throughout most of Southeast Asia and modest gains in northern China and some parts in India, which could be related to land-use and land-cover changes.