Comparison of prediction performance using statistical postprocessing methods

As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.     

AMSR-E sea surface temperature (SST) charts enhancement

Microwave satellite images used for retrieving sea surface temperatures often have such distortions as noise and blurring of the thermal fronts. An image processing approach based on the Mumford-Shah model of optimal image approximation is considered for the solution to this problem. We divide images into flat areas and frontal zones, and then process these areas separately. Image fragmentation is based on automatic detection of the thermal front lines. SST enhancement in frontal zones is achieved by using image deconvolution methods. It has been shown that SST errors in high gradient areas reach 1–3 °C. The proposed approach can decrease this discrepancy.     

The Pedagogical Benefits of SimCity in Urban Geography Education

This article investigated the pedagogical potential of the SimCity simulation game in an urban geography course. University students used SimCity to build their own cities and applied a wide range of theories to support their urban structures. Moreover, the students critically evaluated the logic and functioning of the SimCity simulation compared to real-world contexts and urban geography principles. The students believed the SimCity activity provided them with opportunities to promote their geographic creativity, resulting in diverse, unique, and interesting cities. The findings demonstrate that the use of SimCity can be an effective tool for geography education.     

Carbon and nitrogen dynamics of the intertidal seagrass, <Emphasis Type="Italic">Zostera japonica</Emphasis>, on the southern coast of the Korean peninsula

Seagrasses require a large amount of nutrient assimilation to support high levels of production, and thus nutrient limitation for growth often occurs in seagrass habitats. Seagrasses can take up nutrients from both the water column and sediments. However, since seagrasses inhabiting in the intertidal zones are exposed to the air during low tide, the intertidal species may exhibit significantly different carbon (C) and nitrogen (N) dynamics compared to the subtidal species. To examine C and N dynamics of the intertidal seagrass, Zostera japonica, C and N content and stable isotope ratios of above- and below-ground tissues were measured monthly at the three intertidal zones in Koje Bay on the southern coast of Korea. The C and N content and stable isotope (δ¹³C and δ¹⁵N) ratios of seagrass tissues exhibited significant seasonal variations. Both leaf and rhizome C content were not significantly correlated with productivity. Leaf δ¹³C values usually exhibited negative correlations with leaf productivity. These results of tissue C content and δ¹³C values suggest that photosynthesis of Z. japonica in the study site was not limited by inorganic C supply, and sufficient inorganic C was provided from the atmosphere. The tissue N content usually exhibited negative correlations with leaf productivity except at the upper intertidal zone, suggesting that Z. japonica growth was probably limited by N availability during high growing season. In the upper intertidal zone, no correlations between leaf productivity and tissue elemental content and stable isotope ratios were observed due to the severely suppressed growth caused by strong desiccation stress.