Performance evaluation of chemistry transport models over India

Using continuous and near-real time measurements of the mass concentrations of black carbon (BC) aerosols near the surface, for a period of 1 year (from January to December 2006) from a network of eight observatories spread over different environments of India, a space-time synthesis is generated. The strong seasonal variations observed, with a winter high and summer low, are attributed to the combined effects of changes in synoptic air mass types, modulated strongly by the atmospheric boundary layer dynamics. Spatial distribution shows much higher BC concentration over the Indo-Gangetic Plain (IGP) than the peninsular Indian stations. These were examined against the simulations using two chemical transport models, GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) and CHIMERE for the first time over Indian region. Both the model simulations significantly deviated from the measurements at all the stations; more so during the winter and pre-monsoon seasons and over mega cities. However, the CHIMERE model simulations show better agreement compared with the measurements. Notwithstanding this, both the models captured the temporal variations; at seasonal and subseasonal timescales and the natural variabilities (intra-seasonal oscillations) fairly well, especially at the off-equatorial stations. It is hypothesized that an improvement in the atmospheric boundary layer (ABL) parameterization scheme for tropical environment might lead to better results with GOCART.

Large scale features and assessment of spatial scale correspondence between TMPA and IMD rainfall datasets over Indian landmass

Daily rainfall datasets of 10 years (1998-2007) of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (similar to 0.9) when the study was confined to specific wet and dry spells each of about 5-8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30-50 days and 10-20 days), to be ranging respectively between similar to 30-40% and 5-10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by similar to 110 mm during southwest monsoon and overestimating by similar to 150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1 degrees x1 degrees grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5 degrees x5 degrees average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.

Assessing severe Drought and wet events over India in a future climate using a nested bias-correction approach

General circulation models (GCMs) are routinely used to simulate future climatic conditions. However, rainfall outputs from GCMs are highly uncertain in preserving temporal correlations, frequencies, and intensity distributions, which limits their direct application for downscaling and hydrological modeling studies. To address these limitations, raw outputs of GCMs or regional climate models are often bias corrected using past observations. In this paper, a methodology is presented for using a nested bias-correction approach to predict the frequencies and occurrences of severe droughts and wet conditions across India for a 48-year period (2050-2099) centered at 2075. Specifically, monthly time series of rainfall from 17 GCMs are used to draw conclusions for extreme events. An increasing trend in the frequencies of droughts and wet events is observed. The northern part of India and coastal regions show maximum increase in the frequency of wet events. Drought events are expected to increase in the west central, peninsular, and central northeast regions of India. (C) 2013 American Society of Civil Engineers.

An asymptotically optimal push-pull method for multicasting over a random network

We consider multicast flow problems where either all of the nodes or only a subset of the nodes may be in session. Traffic from each node in the session has to be sent to every other node in the session. If the session does not consist of all the nodes, the remaining nodes act as relays. The nodes are connected by undirected edges whose capacities are independent and identically distributed random variables. We study the asymptotics of the capacity region (with network coding) in the limit of a large number of nodes, and show that the normalized sum rate converges to a constant almost surely. We then provide a decentralized push-pull algorithm that asymptotically achieves this normalized sum rate.

Scheduling for Stable and Reliable Communication Over Multiaccess Channels and Degraded Broadcast Channels

We model communication of bursty sources: 1) over multiaccess channels, with either independent decoding or joint decoding and 2) over degraded broadcast channels, by a discrete-time multiclass processor sharing queue. We utilize error exponents to give a characterization of the processor sharing queue. We analyze the processor sharing queue model for the stable region of message arrival rates, and show the existence of scheduling policies for which the stability region converges to the information-theoretic capacity region in an appropriate limiting sense.

Characterization and Space-Time Downscaling of the Inundation Extent over the Inner Niger Delta Using GIEMS and MODIS Data

The objective in this work is to develop downscaling methodologies to obtain a long time record of inundation extent at high spatial resolution based on the existing low spatial resolution results of the Global Inundation Extent from Multi-Satellites (GIEMS) dataset. In semiarid regions, high-spatial-resolution a priori information can be provided by visible and infrared observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). The study concentrates on the Inner Niger Delta where MODIS-derived inundation extent has been estimated at a 500-m resolution. The space-time variability is first analyzed using a principal component analysis (PCA). This is particularly effective to understand the inundation variability, interpolate in time, or fill in missing values. Two innovative methods are developed (linear regression and matrix inversion) both based on the PCA representation. These GIEMS downscaling techniques have been calibrated using the 500-m MODIS data. The downscaled fields show the expected space-time behaviors from MODIS. A 20-yr dataset of the inundation extent at 500 m is derived from this analysis for the Inner Niger Delta. The methods are very general and may be applied to many basins and to other variables than inundation, provided enough a priori high-spatial-resolution information is available. The derived high-spatial-resolution dataset will be used in the framework of the Surface Water Ocean Topography (SWOT) mission to develop and test the instrument simulator as well as to select the calibration validation sites (with high space-time inundation variability). In addition, once SWOT observations are available, the downscaled methodology will be calibrated on them in order to downscale the GIEMS datasets and to extend the SWOT benefits back in time to 1993.

Reduced Grobner bases and Macaulay-Buchberger Basis Theorem over Noetherian rings

In this paper, we extend the characterization of Zx]/(f), where f is an element of Zx] to be a free Z-module to multivariate polynomial rings over any commutative Noetherian ring, A. The characterization allows us to extend the Grobner basis method of computing a k-vector space basis of residue class polynomial rings over a field k (Macaulay-Buchberger Basis Theorem) to rings, i.e. Ax(1), ... , x(n)]/a, where a subset of Ax(1), ... , x(n)] is an ideal. We give some insights into the characterization for two special cases, when A = Z and A = ktheta(1), ... , theta(m)]. As an application of this characterization, we show that the concept of Border bases can be extended to rings when the corresponding residue class ring is a finitely generated, free A-module. (C) 2014 Elsevier B.V. All rights reserved.

Variability of cloud liquid water and ice over South Asia from TMI estimates

In this study, the Tropical Rainfall Measurement Mission based Microwave Imager estimates (2A12) have been used to compare and contrast the characteristics of cloud liquid water and ice over the Indian land region and the ocean surrounding it, during the premonsoon (May) and monsoon (June-September) seasons. Based on the spatial homogeneity of rainfall, we have selected five regions for our study (three over ocean, two over land). Comparison across three ocean regions suggests that the cloud liquid water (CLW) over the orographically influenced Arabian Sea (close to the Indian west coast) behaves differently from the CLW over a trapped ocean (Bay of Bengal) or an open ocean (equatorial Indian Ocean). Specifically, the Arabian Sea region shows higher liquid water for a lower range of rainfall, whereas the Bay of Bengal and the equatorial Indian Ocean show higher liquid water for a higher range of rainfall. Apart from geographic differences, we also documented seasonal differences by comparing CLW profiles between monsoon and premonsoon periods, as well as between early and peak phases of the monsoon. We find that the CLW during the lean periods of rainfall (May or June) is higher than during the peak and late monsoon season (July-September) for raining clouds. As active and break phases are important signatures of the monsoon progression, we also analysed the differences in CLW during various phases of the monsoon, namely, active, break, active-to-break and break-to-active transition phases. We find that the cloud liquid water content during the break-to-active transition phase is significantly higher than during the active-to-break transition phase over central India. We speculate that this could be attributed to higher amount of aerosol loading over this region during the break phase. We lend credence to this aerosol-CLW/rain association by comparing the central Indian CLW with that over southeast Asia (where the aerosol loading is significantly smaller) and find that in the latter region, there are no significant differences in CLW during the different phases of the monsoon. While our hypothesis needs to be further investigated with numerical models, the results presented in this study can potentially serve as a good benchmark in evaluating the performance of cloud resolving models over the Indian region.

Top Yukawa coupling measurement with indefinite CP Higgs in e(+)e(-) -> t(t)over-bar Phi

We consider the issue of the top quark Yukawa coupling measurement in a model-independent and general case with the inclusion of CP violation in the coupling. Arguably the best process to study this coupling is the associated production of the Higgs boson along with a t (t) over bar pair in a machine like the International Linear Collider (ILC). While detailed analyses of the sensitivity of the measurement-assuming a Standard Model (SM)-like coupling is available in the context of the ILC-conclude that the coupling could be pinned down to about a 10% level with modest luminosity, our investigations show that the scenario could be different in the case of a more general coupling. The modified Lorentz structure resulting in a changed functional dependence of the cross section on the coupling, along with the difference in the cross section itself leads to considerable deviation in the sensitivity. Our studies of the ILC with center-of-mass energies of 500 GeV, 800 GeV, and 1000 GeV show that moderate CP mixing in the Higgs sector could change the sensitivity to about 20%, while it could be worsened to 75% in cases which could accommodate more dramatic changes in the coupling. Detailed considerations of the decay distributions point to a need for a relook at the analysis strategy followed for the case of the SM, such as for a model-independent analysis of the top quark Yukawa coupling measurement. This study strongly suggests that a joint analysis of the CP properties and the Yukawa coupling measurement would be the way forward at the ILC and that caution must be exercised in the measurement of the Yukawa couplings and the conclusions drawn from it.

A media access and feedback protocol for reliable multicast over wireless channel

A link level reliable multicast requires a channel access protocol to resolve the collision of feedback messages sent by multicast data receivers. Several deterministic media access control protocols have been proposed to attain high reliability, but with large delay. Besides, there are also protocols which can only give probabilistic guarantee about reliability, but have the least delay. In this paper, we propose a virtual token-based channel access and feedback protocol (VTCAF) for link level reliable multicasting. The VTCAF protocol introduces a virtual (implicit) token passing mechanism based on carrier sensing to avoid the collision between feedback messages. The delay performance is improved in VTCAF protocol by reducing the number of feedback messages. Besides, the VTCAF protocol is parametric in nature and can easily trade off reliability with the delay as per the requirement of the underlying application. Such a cross layer design approach would be useful for a variety of multicast applications which require reliable communication with different levels of reliability and delay performance. We have analyzed our protocol to evaluate various performance parameters at different packet loss rate and compared its performance with those of others. Our protocol has also been simulated using Castalia network simulator to evaluate the same performance parameters. Simulation and analytical results together show that the VTCAF protocol is able to considerably reduce average access delay while ensuring very high reliability at the same time.

Room Temperature Growth of Ultrathin Au Nanowires with High Areal Density over Large Areas by in Situ Functionalization of Substrate

Although ultrathin Au nanowires (similar to 2 nm diameter) are expected to demonstrate several interesting properties, their extreme fragility has hampered their use in potential applications. One way to improve the stability is to grow them on substrates; however, there is no general method to grow these wires over large areas. The existing methods suffer from poor coverage and associated formation of larger nanoparticles on the substrate. Herein, we demonstrate a room temperature method for growth of these nanowires with high coverage over large areas by in situ functionalization of the substrate. Using control experiments, we demonstrate that an in situ functionalization of the substrate is the key step in controlling the areal density of the wires on the substrate. We show that this strategy works for a variety of substrates ranging like graphene, borosil glass, Kapton, and oxide supports. We present initial results on catalysis using the wires grown on alumina and silica beads and also extend the method to lithography-free device fabrication. This method is general and may be extended to grow ultrathin Au nanowires on a variety of substrates for other applications.

Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data

Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.

Wall-mode instability in plane shear flow of viscoelastic fluid over a deformable solid

The linear stability analysis of a plane Couette flow of an Oldroyd-B viscoelastic fluid past a flexible solid medium is carried out to investigate the role of polymer addition in the stability behavior. The system consists of a viscoelastic fluid layer of thickness R, density rho, viscosity eta, relaxation time lambda, and retardation time beta lambda flowing past a linear elastic solid medium of thickness HR, density rho, and shear modulus G. The emphasis is on the high-Reynolds-number wall-mode instability, which has recently been shown in experiments to destabilize the laminar flow of Newtonian fluids in soft-walled tubes and channels at a significantly lower Reynolds number than that for flows in rigid conduits. For Newtonian fluids, the linear stability studies have shown that the wall modes become unstable when flow Reynolds number exceeds a certain critical value Re c which scales as Sigma(3/4), where Reynolds number Re = rho VR/eta, V is the top-plate velocity, and dimensionless parameter Sigma = rho GR(2)/eta(2) characterizes the fluid-solid system. For high-Reynolds-number flow, the addition of polymer tends to decrease the critical Reynolds number in comparison to that for the Newtonian fluid, indicating a destabilizing role for fluid viscoelasticity. Numerical calculations show that the critical Reynolds number could be decreased by up to a factor of 10 by the addition of small amount of polymer. The critical Reynolds number follows the same scaling Re-c similar to Sigma(3/4) as the wall modes for a Newtonian fluid for very high Reynolds number. However, for moderate Reynolds number, there exists a narrow region in beta-H parametric space, corresponding to very dilute polymer solution (0.9 less than or similar to beta < 1) and thin solids (H less than or similar to 1.1), in which the addition of polymer tends to increase the critical Reynolds number in comparison to the Newtonian fluid. Thus, Reynolds number and polymer properties can be tailored to either increase or decrease the critical Reynolds number for unstable modes, thus providing an additional degree of control over the laminar-turbulent transition.

Modeling non-stationarity in intensity, duration and frequency of extreme rainfall over India

Significant changes are reported in extreme rainfall characteristics over India in recent studies though there are disagreements on the spatial uniformity and causes of trends. Based on recent theoretical advancements in the Extreme Value Theory (EVT), we analyze changes in extreme rainfall characteristics over India using a high-resolution daily gridded (1 degrees latitude x 1 degrees longitude) dataset. Intensity, duration and frequency of excess rain over a high threshold in the summer monsoon season are modeled by non-stationary distributions whose parameters vary with physical covariates like the El-Nino Southern Oscillation index (ENSO-index) which is an indicator of large-scale natural variability, global average temperature which is an indicator of human-induced global warming and local mean temperatures which possibly indicate more localized changes. Each non-stationary model considers one physical covariate and the best chosen statistical model at each rainfall grid gives the most significant physical driver for each extreme rainfall characteristic at that grid. Intensity, duration and frequency of extreme rainfall exhibit non-stationarity due to different drivers and no spatially uniform pattern is observed in the changes in them across the country. At most of the locations, duration of extreme rainfall spells is found to be stationary, while non-stationary associations between intensity and frequency and local changes in temperature are detected at a large number of locations. This study presents the first application of nonstationary statistical modeling of intensity, duration and frequency of extreme rainfall over India. The developed models are further used for rainfall frequency analysis to show changes in the 100-year extreme rainfall event. Our findings indicate the varying nature of each extreme rainfall characteristic and their drivers and emphasize the necessity of a comprehensive framework to assess resulting risks of precipitation induced flooding. (C) 2014 Elsevier B.V. All rights reserved.

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.