ALBERT

Description: Total column ozone variations estimated using ground-based stations provide important independent source of information in addition to satellite-based estimates. This estimation has been vigorously challenged by data inhomogeneity in time and by the irregularity of the spatial distribution of stations, as well as by interruptions in observation records. Furthermore, some stations have calibration issues and thus observations may drift. In this paper we compare the spatial interpolation of ozone levels using the novel stochastic partial differential equation (SPDE) approach with kriging. We show how these new spatial predictions are more accurate, less uncertain and more robust. We construct long-term zonal means to investigate the robustness against the absence of measurements at some stations as well as instruments drifts. We conclude that time series analyzes can benefit from the SPDE approach compared to kriging when stations are missing, but the positive impact of the technique is less pronounced in the case of drifts.

Description: We developed a multi-scale OBIA (object-based image analysis) landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR) of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

Description: This study attempts to achieve real-time rainfall-inundation forecasting in lowland regions, based on a synthetic potential inundation database. With the principal component analysis and a feed-forward neural network, a rainfall-inundation hybrid neural network (RiHNN) is proposed to forecast 1-h-ahead inundation depth as hydrographs at specific representative locations using spatial rainfall intensities and accumulations. A systematic procedure is presented to construct the RiHNN, which combines the merits of detailed hydraulic modeling in flood-prone lowlands via a two-dimensional overland-flow model and time-saving calculation in a real-time rainfall-inundation forecasting via ANN model. Analytical results from the RiHNNs with various principal components indicate that the RiHNNs with fewer weights can have about the same performance as a feed-forward neural network. The RiHNNs evaluated through four types of real/synthetic rainfall events also show to fit inundation-depth hydrographs well with high rainfall. Moreover, the results of real-time rainfall-inundation forecasting help the emergency manager set operational responses, which are beneficial for flood warning preparations.

Description: An ocean buoy, UBIM, deployed during the spring transition from February and May, 2010 reveals for the first time highly-resolved temporal variation of biochemical properties of the upper layer of the Ulleung Basin in the southwestern East/Japan Sea. Meteorological data shows the typical spring transition occurred during the mooring period, weakening of wind speed, increase in shortwave radiation, and change in total heat flux from net cooling to net heating. Power spectrum of chlorophyll fluorescence (CF) peaks at semidiurnal tidal, near-inertial, diurnal, and subtidal frequencies. The diurnal variation of CF is characterized by high CF during the daytime and low CF at night. Dissolved oxygen and CF are correlated with high (low) dissolved oxygen accompanied by high (low) CF, indicating the dissolved oxygen is mainly determined by biological activities. The time series measurement captured the onset of subsurface spring bloom at 30 m, and collocated temperature and current data gives an insight into a mechanism that triggers the onset of the spring bloom not documented so far. The entire mooring period can be divided into pre-bloom period from the beginning of the mooring to early April, and bloom period afterwards. Mean CF values during the pre-bloom and bloom periods are 0.9 μg L−1 and 1.9 μg L−1, respectively. Mean mixed layer depth (MLD) shoaled from 22 m during the pre-bloom period to 15 m during the bloom period. Despite of the increase in shortwave radiation, average PAR values at 20 m show lower value during the bloom period as compared to that during the pre-bloom period. Low-frequency modulation of MLD ranging from 10 m to 53 m during the entire mooring period is mainly determined by shoaling and deepening of isothermal (isopycnal) depths. Temperature structure in the upper 110 m is characterized by alternating uplifting and lowering of isotherms, which is caused by the placement of the mooring site on the cold (cyclonic) or warm side of the frontal jet, the East Korean Warm Current. The frontal variability is thought to be due to the low-frequency path variatio of the East Korean Warm Current. The occurrence of the spring bloom at 30 m is concomitant with the appearance of colder East Sea Intermediate Water (ESIW) at buoy UBIM that results in the subsurface cooling and the shoaling of isotherms to the shallower depth levels than those occurred during the pre-bloom period. It is suggested that the springtime spreading of the ESIW is one of the important factors that triggers the onset of subsurface spring bloom below the mixed layer. The time lag between the peaks of CF and the occurrence of the shallowest isothermal depths is about several days, which appears to be the timescale for the growth of phytoplankton.

Description: An ocean buoy, UBIM (Ulleung Basin Integrated Mooring), deployed during the spring transition from February to May 2010 reveals for the first time highly resolved temporal variation of biochemical properties of the upper layer of the Ulleung Basin in the southwestern East Sea/Sea of Japan. The time-series measurement captured the onset of subsurface spring bloom at 30 m, and collocated temperature and current data gives an insight into a mechanism that triggers the onset of the spring bloom not documented so far. Low-frequency modulation of the mixed layer depth ranging from 10 m to 53 m during the entire mooring period is mainly determined by shoaling and deepening of isothermal depths depending on the placement of UBIM on the cold or warm side of the frontal jet. The occurrence of the spring bloom at 30 m is concomitant with the appearance of colder East Sea Intermediate Water at buoy UBIM, which results in subsurface cooling and shoaling of isotherms to the shallower depth levels during the bloom period than those that occurred during the pre-bloom period. Isolines of temperature-based NO3 are also shown to be uplifted during the bloom period. It is suggested that the springtime spreading of the East Sea Intermediate Water is one of the important factors that triggers the subsurface spring bloom below the mixed layer.

Description: Total column ozone variations estimated using ground-based stations provide important independent source of information in addition to satellite-based estimates. This estimation has been vigorously challenged by data inhomogeneity in time and by the irregularity of the spatial distribution of stations, as well as by interruptions in observation records. Furthermore, some stations have calibration issues and thus observations may drift. In this paper we compare the spatial interpolation of ozone levels using the novel stochastic partial differential equation (SPDE) approach with the covariance-based kriging. We show how these new spatial predictions are more accurate, less uncertain and more robust. We construct long-term zonal means to investigate the robustness against the absence of measurements at some stations as well as instruments drifts. We conclude that time series analyzes can benefit from the SPDE approach compared to the covariance-based kriging when stations are missing, but the positive impact of the technique is less pronounced in the case of drifts.