<Emphasis Type="Italic">Cochlodinium polykrikoides</Emphasis> red tide detection in the South Sea of Korea using spectral classification of MODIS data

To distinguish true red tide water (particularly Cochlodinium polykrikoides blooms) from non-red tide water (false satellite high chlorophyll water) in the South Sea of Korea, we developed a systematic classification method using spectral information from MODIS level products and applied it to five different harmful algal bloom events. Red tide and nonred tide waters were classified based on four different criteria. The first step revealed that the radiance peaks of potential red tide water occurred at 555 and 678 nm. The second step separated optically different waters that were influenced by relatively low and high contributions of colored dissolved organic matter (CDOM) (including detritus) to chlorophyll. The third and fourth steps discriminated red tide water from non-red tide water based on the blue-to-green ratio in areas with lower and higher contributions of CDOM to chlorophyll, respectively. After applying the red tide classification (using the four criteria), the spectral response of the red tide water, which is influenced by pigment concentration, showed different slopes for the blue and green bands (lower slope at blue bands and higher slope at green bands). The opposite result was found for non-red tide water, due to decreasing phytoplankton absorption and increasing detritus/CDOM absorption at blue bands. The results were well matched with the discoloration of water (blue to dark red/brown) and delineated the areal coverage of C. polykrikoides blooms, revealing the nature of spatial and temporal variations in red tides. This simple spectral classification method led to increase user accuracy for C. polykrikoides and non-red tide blooms (>46% and >97%) and provided a more reliable and robust identification of red tides over a wide range of oceanic environments than was possible using chlorophyll a concentration, chlorophyll anomaly, fluorescence analysis, or proposed red tide detection algorithms.     

Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery

Monitoring crop conditions and forecasting crop yields are both important for assessing crop production and for determining appropriate agricultural management practices; however, remote sensing is limited by the resolution, timing, and coverage of satellite images, and crop modeling is limited in its application at regional scales. To resolve these issues, the Gramineae (GRAMI)-rice model, which utilizes remote sensing data, was used in an effort to combine the complementary techniques of remote sensing and crop modeling. The model was then investigated for its capability to monitor canopy growth and estimate the grain yield of rice (Oryza sativa), at both the field and the regional scales, by using remote sensing images with high spatial resolution. The field scale investigation was performed using unmanned aerial vehicle (UAV) images, and the regional-scale investigation was performed using RapidEye satellite images. Simulated grain yields at the field scale were not significantly different (p = 0.45, p = 0.27, and p = 0.52) from the corresponding measured grain yields according to paired t-tests (α = 0.05). The model’s projections of grain yield at the regional scale represented the spatial grain yield variation of the corresponding field conditions to within ±1 standard deviation. Therefore, based on mapping the growth and grain yield of rice at both field and regional scales of interest within coverages of a UAV or the RapidEye satellite, our results demonstrate the applicability of the GRAMI-rice model to the monitoring and prediction of rice growth and grain yield at different spatial scales. In addition, the GRAMI-rice model is capable of reproducing seasonal variations in rice growth and grain yield at different spatial scales.     

Estimation of periodicities in hydrologic data

Periodicites in hydrologic data are frequently estimated and studied. In some cases the periodic components are subtracted from the data to obtain the stochastic components. In other cases the physical reasons for the occurrence of these periodicities are investigated. Apart from the annual cycle in the hydrologic data, periods corresponding to the 11 year sunspot cycle, the Hale cycle and others have been detected.The conclusions from most of these studies depend on the reliability and robustness of the methods used to detect these periodicities. Several spectral analysis methods have been proposed to investigate periodicities in time series data. Several of these have been compared to each other. The methods by Siddiqui and Wang and by Damsleth and Spjotvoll, which are stepwise procedures of spectrum estimation, have not been evaluated.     

The evaluation of the probability of rock wedge failure using the point estimate method

In a probabilistic analysis of rock slope stability, the Monte Carlo simulation technique has been widely used to evaluate the probability of slope failure. While the Monte Carlo simulation technique has many advantages, the technique requires complete information of the random variables in stability analysis; however, in practice, it is difficult to obtain complete information from a field investigation. The information on random variables is usually limited due to the restraints of sampling numbers. This is why approximation methods have been proposed for reliability analyses. Approximation methods, such as the first-order second-moment method and the point estimate method, require only the mean and standard deviation of the random variable; therefore, it is easy to utilize when the information is limited. Usually, a single closed form of the formula for the evaluation of the factor of safety is needed for an approximation method. However, the commonly used stability analysis method of wedge failure is complicated and cumbersome and does not provide a simple equation for the evaluation of the factor of safety. Consequently, the approximation method is not appropriate for wedge failure. In order to overcome this limitation, a simple equation, which is obtained from the maximum likelihood estimation method for wedge failure, is utilized to calculate the probability of failure. A simple equation for the direct estimation of the safety factors for wedge failure has been empirically derived from failed and stable cases of slope, using the maximum likelihood estimation method. The developed technique has been applied to a practical example, and the results from the developed technique were compared to the results from the Monte Carlo simulation technique.     

New dinosaur tracks from Korea, Ornithopodichnus masanensis ichnogen. et ichnosp. nov. (Jindong Formation, Lower Cretaceous): implications for polarities in ornithopod foot morphology

Twelve trackways of ornithopods from Lower Cretaceous lacustrine margin deposits of the Jindong Formation represent new dinosaur trackways described from Korea. The site, discovered during highway construction, was rescued by removing the most important trackways to the Korean Natural Heritage Center in Daejeon, where they are on permanent display. The new ichnotaxon Ornithopodichnus masanensis ichnogen. et ichnosp. nov. is recognized as a distinctive robust tridactyl track, slightly wider than long (l/w ratio = 0.91), with positive (inward) rotation. The toe prints are very thick, broad and U-shaped, resulting in a trefoil outline with a smoothly rounded hind margin. Digit III is short and projects anteriorly much less than digit II and IV (= weak mesaxony). Divarication of digits II-IV is about 70° with interdigital angle II-III larger than III-IV. Trackway width is narrow and the stride length/track length ratio is about 4.2–4.6. The Ornithopodichnus trackways evidently represent gregarious blunt-toed Iguanodon-like bipedal ornithopods, although poorly preserved manus traces are discerned in a few trackways. Ornithopodichnus is distinct from other well known iguanodontid tracks that display much stronger mesaxony and indicates a polarity in ornithopod foot morphology that can be verified by reference to known foot skeletons.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

Impact of vegetation feedback on the temperature and its diurnal range over the Northern Hemisphere during summer in a 2 × CO2 climate

This study examines the potential impact of vegetation feedback on the changes in the diurnal temperature range (DTR) due to the doubling of atmospheric CO₂ concentrations during summer over the Northern Hemisphere using a global climate model equipped with a dynamic vegetation model. Results show that CO₂ doubling induces significant increases in the daily mean temperature and decreases in DTR regardless of the presence of the vegetation feedback effect. In the presence of vegetation feedback, increase in vegetation productivity related to warm and humid climate lead to (1) an increase in vegetation greenness in the mid-latitude and (2) a greening and the expansion of grasslands and boreal forests into the tundra region in the high latitudes. The greening via vegetation feedback induces contrasting effects on the temperature fields between the mid- and high-latitude regions. In the mid-latitudes, the greening further limits the increase in T _max more than T _min, resulting in further decreases in DTR because the greening amplifies evapotranspiration and thus cools daytime temperature. The greening in high-latitudes, however, it reinforces the warming by increasing T _max more than T _min to result in a further increase in DTR from the values obtained without vegetation feedback. This effect on T _max and DTR in the high latitude is mainly attributed to the reduction in surface albedo and the subsequent increase in the absorbed insolation. Present study indicates that vegetation feedback can alter the response of the temperature field to increases in CO₂ mainly by affecting the T _max and that its effect varies with the regional climate characteristics as a function of latitudes.