Circulation characteristics of a monsoon depression during BOBMEX-99 using high-resolution analysis

The skill and efficiency of a numerical model mostly varies with the quality of initial values, accuracy on parameterization of physical processes and horizontal and vertical resolution of the model. Commonly used low-resolution reanalyses are hardly able to capture the prominent features associated with organized convective processes in a monsoon depression. The objective is to prepare improved high-resolution analysis by the use of MM5 modelling system developed by the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR). It requires the objective comparison of high and low-resolution analysis datasets in assessing the specific convective features of a monsoon depression. For this purpose, reanalysis datasets of NCAR/NCEP (National Center for Atmospheric Research/National Centers for Environmental Prediction) at a horizontal resolution of 2.5‡ (latitude/longitude) have been used as first guess in the objective analysis scheme. The additional asynoptic datasets obtained during BOBMEX-99 are utilized within the assimilation process. Cloud Motion Wind (CMW) data of METEOSAT satellite and SSM/I surface wind data are included for the improvement of derived analysis. The multiquadric (MQD) interpolation technique is selected and applied for meteorological objective analysis at a horizontal resolution of 30 km. After a successful inclusion of additional data, the resulting reanalysis is able to produce the structure of convective organization as well as prominent synoptic features associated with monsoon depression. Comparison and error verifications have been done with the help of available upper-air station data. The objective verification reveals the efficiency of the analysis scheme.     

Regional planning in the U.S.S.R.: Methodological principles and practice

Regional planning in the U.S.S.R. is part of a comprehensive and hierarchical spatial and sectoral planning system. Four levels are described: (a) the national level, involving the total settlement system; (b) the major regional level, handling major development schemes; (c) the minor regional level, with plans for administrative districts; and (d) the urban level, where city master plans are produced. The amount of detail and scale of working increased downwards through the hierarchy. The most pressing problem is planning for the emergence and growth of cities of 100,000 population or more. Moscow city-region is used as an illustration.     

Towards Stochastic Time-Varying Geological Modeling

The modeling of subsurface geometry and properties is a key element to understand Earth processes and manage natural hazards and resources. In this paper, we suggest this field should evolve beyond pure data fitting approaches by integrating geological concepts to constrain interpretations or test their consistency. This process necessarily calls for adding the time dimension to 3D modeling, both at the geological and human time scales. Also, instead of striving for one single best model, it is appropriate to generate several possible subsurface models in order to convey a quantitative sense of uncertainty. Depending on the modeling objective (e.g., quantification of natural resources, production forecast), this population of models can be ranked. Inverse theory then provides a framework to validate (or rather invalidate) models which are not compatible with certain types of observations. We review recent methods to better achieve both stochastic and time-varying geomodeling and advocate that the application of inversion should rely not only on random field models, but also on geological concepts and parameters.     

Model-based covariance mean variance classification techniques:algorithm development and application to the acoustic classification ofzooplankton

For inversion problems in which the theoretical relationship between observed data and model parameters is well characterized, a promising approach to the classification problem is the application of techniques that capitalize on the predictive power of class-specific models. Theoretical models have been developed for three zooplankton scattering classes (hard elastic-shelled, e.g., pteropods; fluid-like, e.g., euphausiids; and gas-bearing, e.g., siphonophores), providing a sound basis for model-based classification approaches. The covariance mean variance classification (CMVC) techniques classify broad-band echoes from individual zooplankton based on comparisons of observed echo spectra to model space realizations. Three different CMVC algorithms were developed: the integrated score classifier, the pairwise score classifier, and the Bayesian probability classifier; these classifiers assign observations to a class based on similarities in covariance, mean, and variance while accounting for model spare ambiguity and validity. The CMVC techniques were applied to broad-band (~350-750 kHz) echoes acquired from 24 different zooplankton to invert for scatterer class and properties. All three classification algorithms had a high rate of success with high-quality high SNR data. Accurate acoustic classification of zooplankton species has the potential to significantly improve estimates of zooplankton biomass made from ocean acoustic backscatter measurements     

Combining pixel and object based image analysis of ultra-high resolution multibeam bathymetry and backscatter for habitat mapping in shallow marine waters

Habitat mapping data are increasingly being recognised for their importance in underpinning marine spatial planning. The ability to collect ultra-high resolution (cm) multibeam echosounder (MBES) data in shallow waters has facilitated understanding of the fine-scale distribution of benthic habitats in these areas that are often prone to human disturbance. Developing quantitative and objective approaches to integrate MBES data with ground observations for predictive modelling is essential for ensuring repeatability and providing confidence measures for habitat mapping products. Whilst supervised classification approaches are becoming more common, users are often faced with a decision whether to implement a pixel based (PB) or an object based (OB) image analysis approach, with often limited understanding of the potential influence of that decision on final map products and relative importance of data inputs to patterns observed. In this study, we apply an ensemble learning approach capable of integrating PB and OB Image Analysis from ultra-high resolution MBES bathymetry and backscatter data for mapping benthic habitats in Refuge Cove, a temperate coastal embayment in south-east Australia. We demonstrate the relative importance of PB and OB seafloor derivatives for the five broad benthic habitats that dominate the site. We found that OB and PB approaches performed well with differences in classification accuracy but not discernible statistically. However, a model incorporating elements of both approaches proved to be significantly more accurate than OB or PB methods alone and demonstrate the benefits of using MBES bathymetry and backscatter combined for class discrimination.     

A record of long-time rift activity and earthquake-induced ground effects in Pleistocene deposits of southern Tenerife (Canary Islands,Spain)

Faults with a well-defined strike direction that precisely coincides with the southern rift fault system occur in the study area in southern Tenerife. This fault system was generated contemporaneously with a chain of cinder cones ~948 ka. Open fractures in ignimbrites (~668 ka) and fossil beach deposits (~42 ka) of the El Médano area suggest that the rift-associated fault system was seismically active in the aftermath of the initial volcanic activity (~948 ka) and is probably still active. A second fault system striking perpendicular to the rift-related faults probably originates from a Holocene paleoearthquake of moderate intensity. Earthquake-induced ground effects in fossil beach deposits within the study area are consistent with seismically induced ground effects of several recent and well-documented earthquakes, as well as gravitational sliding triggered by an intense earthquake in the Nicoya Peninsula of Costa Rica in 1990. Both, the rift-associated and the earthquake-induced fault system, initially produced open fractures that were occupied by plants and subsequently stabilized by cementation, forming conspicuous sediment structures in fossil beach deposits of the El Médano site in southern Tenerife.     

Vertical double silicate maxima in the sea-ice reduction region of the western Arctic Ocean: Implications for an enhanced biological pump due to sea-ice reduction

The R/V Mirai conducted hydrographic surveys in the western Arctic Ocean during summer 2004 (Mirai04) over wide east-west ranges from Alaska to eastern Siberia, where sea-ice cover has been greatly reduced in recent summers. The obtained data reveal differences in silicate profiles between shelf slope areas east and west of the Chukchi Plateau, the ridge that divides the Canada Basin into the Alaskan and east Siberian sides. East of the plateau, a single silicate maximum was found in a layer of Pacific-origin winter water, as examined in many previous studies. In contrast, west of the plateau, we found vertical double silicate maxima, which are reported for the first time in this study. The shallower silicate maximum corresponded to an N** minimum, signaling denitrification at the shelf bottom. This suggests that the shallower silicate maximum was caused by the spreading of shelf water. In contrast, the deeper silicate maximum corresponded to an oxygen minimum and a maximum silicate/phosphate ratio (Si/P), suggesting that this deeper maximum resulted from the decomposition of opal-shelled organisms. We also compared a silicate profile from Mirai04 to aprofile from the Arctic Ocean Section 94 (AOS94) expedition of 1994, a heavy ice year. The results suggest that sea-ice loss has enhanced biological activities, likely resulting in the appearance of the deeper silicate maximum.     

The Impact of Hurricane Katrina on the Coastal Vegetation of the Weeks Bay Reserve,Alabama from NDVI Data

Normalized Difference Vegetation Index (NDVI) data were used to investigate vegetation changes after Hurricane Katrina (2005) for the Weeks Bay Reserve and surrounding area of coastal AL. Landsat 5 satellite images were acquired before landfall (March 24, 2005), after landfall (September 16, 2005), and 8 months after landfall (April 28, 2006). The March 2005 to September 2005 image comparison showed that average NDVI values decreased by 49% after landfall. Continuing into the next year, average NDVI values were −44% lower in April 2006 than they were in March 2005. Among habitat types, the estuarine emergent wetland experienced the largest average NDVI value decrease (−64%). The estuarine emergent wetland NDVI values continued to decrease by −27% from September 2005 to April 2006, whereas other habitats increased in NDVI. This continued suppression of NDVI values was attributed to increased salinity from the storm surge and to regional drought conditions that occurred after landfall. These results provide insight into the sensitivity of coastal vegetation from the interactions of both tropical cyclones and long-term environmental conditions.