Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold’s SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold’s and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold’s SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold’s SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold’s SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.     

Respiration of Recently-Fixed Plant Carbon Dominates Mid-Winter Ecosystem CO2 Production in Sub-Arctic Heath Tundra

Arctic ecosystems could provide a substantial positive feedback to global climate change if warming stimulates below-ground CO₂ release by enhancing decomposition of bulk soil organic matter reserves.Ecosystem respiration during winter is important in this context because CO₂ release from snow-covered tundra soils is a substantial component of annual net carbon (C) balance, and because global climate models predict that the most rapid rises in regional air temperature will occur in the Arctic during winter. In this manipulative field study, the relative contributions of plant and bulk soil organic matter C pools to ecosystem CO₂ production in mid-winter were investigated. We measured CO₂ efflux rates in Swedish sub-arctic heath tundra from control plots and from plots that had been clipped in the previous growing season to disrupt plant activity. Respiration derived from recently-fixed plant C (i.e., plant respiration, and respiration associated with rhizosphere exudates and decomposition of fresh litter) was the principal source of CO₂ efflux, while respiration associated with decomposition of bulk soil organic matter was low, and appeared relatively insensitive to temperature. These results suggest that warmer mid-winter temperatures in the Arctic may have a much greater impact on the cycling of recently-fixed, plant-associated C pools than on the depletion of tundra bulk soil C reserves, and consequently that there is a low potential for significant initial feedbacks from arctic ecosystems to climate change during mid-winter.     

Conventions on thermal expansion modelling of radio telescopes for geodetic and astrometric VLBI

Thermal expansion of radio telescopes has long been recognized as an effect which cannot be neglected in geodetic and astrometric VLBI data analysis if millimeter accuracy is desired. In this article, the author documents the conventions which are being set by the International VLBI Service for Geodesy and Astrometry (IVS) for a consistent modelling of this effect in its routine product generation. For the largest telescopes, the annual cycle of thermal expansion may change the height of the VLBI reference point by as much as 20 mm. However, for telescopes which are used in present-day IVS operations, the variations rather range from 4 to 6 mm.     

Recovery of groundwater in the Sanriku region contaminated by the tsunami inundation from the 2011 Tohoku earthquake

Many wells in the Sanriku region used as sources for water supply systems were heavily contaminated by the tsunami of the 2011 great Tohoku earthquake on March 11 in 2011. To better understand the nature of the groundwater contamination by the tsunami inundation and to clarify the recovery process of contaminated groundwater at the study wells, groundwater monitoring has been conducted once or twice yearly since early summer in 2011. High and abnormal values of electric conductivity (EC), chloride ion concentration (CIC), Na⁺, Ca⁺, heavy metal ions, and heavier isotopes of the contaminated groundwater were also obtained in April and June 2011. The chemical elements have rapidly and exponentially decreased as a result of effective pumping of the contaminated groundwater from the study wells and because of abundant rainfall in 2011. In April 2015 (about 4 years after the tsunami inundation), the CIC and EC of the contaminated groundwater of two study wells in Minamisanriku town had reached pre-inundation values. The estimated residence times of groundwater of the two study wells were 105–118 days in the full-day pumping stage and 910–1000 days in the daytime-only pumping stage.     

Evaluation of site effects on ground motions based on equivalent linear site response analysis and liquefaction potential in Chennai,south India

We study local site effects with detailed geotechnical and geophysical site characterization to evaluate the site-specific seismic hazard for the seismic microzonation of the Chennai city in South India. A Maximum Credible Earthquake (MCE) of magnitude 6.0 is considered based on the available seismotectonic and geological information of the study area. We synthesized strong ground motion records for this target event using stochastic finite-fault technique, based on a dynamic corner frequency approach, at different sites in the city, with the model parameters for the source, site, and path (attenuation) most appropriately selected for this region. We tested the influence of several model parameters on the characteristics of ground motion through simulations and found that stress drop largely influences both the amplitude and frequency of ground motion. To minimize its influence, we estimated stress drop after finite bandwidth correction, as expected from an M6 earthquake in Indian peninsula shield for accurately predicting the level of ground motion. Estimates of shear wave velocity averaged over the top 30 m of soil (V_S30) are obtained from multichannel analysis of surface wave (MASW) at 210 sites at depths of 30 to 60 m below the ground surface. Using these V_S30 values, along with the available geotechnical information and synthetic ground motion database obtained, equivalent linear one-dimensional site response analysis that approximates the nonlinear soil behavior within the linear analysis framework was performed using the computer program SHAKE2000. Fundamental natural frequency, Peak Ground Acceleration (PGA) at surface and rock levels, response spectrum at surface level for different damping coefficients, and amplification factors are presented at different sites of the city. Liquefaction study was done based on the V_S30 and PGA values obtained. The major findings suggest show that the northeast part of the city is characterized by (i) low V_S30 values (<?200 m/s) associated with alluvial deposits, (ii) relatively high PGA value, at the surface, of about 0.24 g, and (iii) factor of safety and liquefaction below unity at three sites (no. 12, no. 37, and no. 70). Thus, this part of the city is expected to experience damage for the expected M6 target event.     

Experimental study of headcut erosion in cohesive soils under different consolidation types and hydraulic parameters

Headcut is a change in stream channel elevation, where there is concentrated flow. Most of the past studies focus on non-cohesive soils, although many problems on the streams occur because of cohesive beds and banks. In this study, eight samples of cohesive soils, with a different composition of silt and clay, for different waterfall heights and flow velocity under long- and short-term natural consolidation conditions were tested. In one of the tests, a sand layer was settled on the headcut bed to investigate its impact on headcut erosion. By increasing clay content, the headcut will remain vertical as it moves backward. Result showed that the effect of clay content reduction was more noticeable under the long-term consolidation condition. In general, the effect of clay percentage variation on the measured parameters is much higher than the effects of waterfall height or flow velocity, and the effect of consolidation type and adding a sand layer on the measured values is much higher than the effect of clay percentage variation on the waterfall height and flow velocity.     

New classes of spectral densities for lattice processes and random fields built from simple univariate margins

Quasi arithmetic and Archimedean functionals are used to build new classes of spectral densities for processes defined on any d-dimensional lattice \mathbbZ^d{\mathbb{Z}^d} and random fields defined on the d-dimensional Euclidean space \mathbbR^d{\mathbb{R}^d}, given simple margins. We discuss the mathematical features of the proposed constructions, and show rigorously as well as through examples, that these new classes of spectra generalize celebrated classes introduced in the literature. Additionally, we obtain permissible spectral densities as linear combinations of quasi arithmetic or Archimedean functionals, whose associated correlation functions may attain negative values or oscillate between positive and negative ones. We finally show that these new classes of spectral densities can be used for nonseparable processes that are not necessarily diagonally symmetric.     

From global to local: Testing the potential of cross-scaling in global data sets

The present study investigates the potential of readily available and easily accessible global data sets to understand regional/local level interactions in wetland systems. The biogeographical zones of India were used a base-frame to select three sites. The study well fits the interests of National Wetland Committee of India to investigate and document fundamental information on wetland extent/distribution. The national partnership with SACON represents this interest. SACON commenced the inland wetland inventory module at national scale using geospatial data, although the provincial scale analysis is underway. In addition, the global irrigated area mapping (GIAM-IWMI) project generated multi-scalar spatial outputs for irrigated/rain-fed areas. With the existing information base, a multi-level geospatial analysis using Arc GIS algorithmic modelling was used to derive comprehensive appraisal of wetland systems complementing the data from GIAM and SACON. It was observed that the overlap between the two layers was 58 percent for Gujarat and 10 percent in Tamil Nadu. In Krishna basin the wetland’s cover 1.04 million hectare excluding the rice agro-ecosystem. The difference in the biogeography of the case sites governs the gradient of information derived from both data layers. Additionally, the global lakes and wetlands database (GLWD) database added thematic information on coastal wetlands. In summary we describe the cross-scaling the global data layers to compliment the regional/national level monitoring assignments.     

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.     

Temporal variability in summertime bottom hypoxia in shallow areas of Mobile Bay,Alabama

This paper addresses temporal variability in bottom hypoxia in broad shallow areas of Mobile Bay, Alabama. Time-series data collected in the summer of 2004 from one station (mean depth of 4 m) exhibit bottom dissolved oxygen (DO) variations associated with various time scales of hours to days. Despite a large velocity shear, stratification was strong enough to suppress vertical mixing most of the time. Bottom DO was closely related to the vertical salinity gradient (ΔS). Hypoxia seldom occurred when ΔS (over 2.5 m) was <2 psu and occurred almost all the time when ΔS was >8 psu in the absence of extreme events like hurricanes. Oxygen balance between vertical mixing and total oxygen demand was considered for bottom water from which oxygen demand and diffusive oxygen flux were estimated. The estimated decay rates at 20°C ranging between 0.175–0.322 d⁻¹ and the corresponding oxygen consumption as large as 7.4 g O₂ m⁻² d⁻¹ fall at the upper limit of previously reported ranges. The diffusive oxygen flux and the corresponding vertical diffusivity estimated for well mixed conditions range between 8.6–9.5 g O₂ m⁻² d⁻¹ and 2.6–2.9 m² d⁻¹, respectively. Mobile Bay hypoxia is likely to be associated with a large oxygen demand, supported by both water column and sediment oxygen demands, so that oxygen supply from surface water during destratification events would be quickly exhausted to return to hypoxic conditions within a few hours to days after destratification events are terminated.