Modeling Indian Ocean circulation: Bay of Bengal fresh water plume and the Arabian Sea Mini Warm Pool

The Indian subcontinent divides the north Indian Ocean into two tropical basins, namely the Arabian Sea and the Bay of Bengal. The Arabian Sea has high salinity whereas the salinity of the Bay of Bengal is much lower due to the contrast in freshwater forcing of the two basins. The freshwater received by the Bay in large amounts during the summer monsoon through river discharge is flushed out annually by ocean circulation. After the withdrawal of the summer monsoon, the Ganga – Brahmaputra river plume flows first along the Indian coast and then around Sri Lanka into the Arabian Sea creating a low salinity pool in the southeastern Arabian Sea (SEAS). In the same region, during the pre-monsoon months of February – April, a warm pool, known as the Arabian Sea Mini Warm Pool (ASMWP), which is distinctly warmer than the rest of the Indian Ocean, takes shape. In fact, this is the warmest region in the world oceans during this period. Simulation of the river plume and its movement as well as its implications to thermodynamics has been a challenging problem for models of Indian Ocean. Here we address these issues using an ocean general circulation model – first we show that the model is capable of reproducing fresh plumes in the Bay of Bengal as well as its movement and then we use the model to determine the processes that lead to formation of the ASMWP. Hydrographic observations from the western Bay of Bengal have shown the presence of a fresh plume along the northern part of the Indian coast during summer monsoon. The Indian Ocean model when forced by realistic winds and climatological river discharge reproduces the fresh plume with reasonable accuracy. The fresh plume does not advect along the Indian coast until the end of summer monsoon. The North Bay Monsoon Current, which flows eastward in the northern Bay, separates the low salinity water from the more saline southern parts of the bay and thus plays an important role in the fresh water budget of the Bay of Bengal. The model also reproduces the surge of the fresh-plume along the Indian coast, into the Arabian Sea during northeast monsoon. Mechanisms that lead to the formation of the Arabian Sea Mini Warm Pool are investigated using several numerical experiments. Contrary to the existing theories, we find that salinity effects are not necessary for the formation of the ASMWP. The orographic effects of the Sahyadris (Western Ghats) and resulting reduction in wind speed leads to the formation of the ASMWP. During November – April, the SEAS behave as a low-wind heatdominated regime where the evolution of sea surface temperature is solely determined by atmospheric forcing. In such regions the evolution of surface layer temperature is not dependent on the characteristics of the subsurface ocean such as the barrier layer and temperature inversion.

Monitoring Himalayan cryosphere using remote sensing techniques

In the Himalayas, large area is covered by glaciers, seasonal snow and changes in its extent can influence availability of water in the Himalayan Rivers. In this paper, changes in glacial extent, glacial mass balance and seasonal snow cover have been discussed. Field and satellite based investigations suggest, most of the Himalayan glaciers are retreating though the rate of retreat is varying from glacier to glacier, ranging from few meters to almost 50 meters per year, depending upon the numerous glacial, terrain and meteorological parameters. Retreat was estimated for 1868 glaciers in eleven basins distributed across the Indian Himalaya since 1962 to 2001/02. Estimates show an overall reduction in glacier area from 6332 to 5329 sq km, an overall deglaciation of 16 percent.Snow line at the end of ablation season on the Chhota Shigri glacier suggests a change in altitude from 4900 to 5200 m from late 1970’s to the present. Seasonal snow cover monitoring of the Himalaya has shown large amounts of snow cover depletion in early part of winter, i.e. from October to December. For many basins located in lower altitude and in south of Pir Panjal range, snow ablation was observed through out the winter season. In addition, average stream runoff of the Baspa basin during the month of December shows an increase by 75 per cent. This combination of glacial retreat, negative mass balance, early melting of seasonal snow cover and winter time increase in stream runoff suggest an influence of climate change on the Himalayan cryosphere.

Characterization of the dynamics of glass-forming liquids from the properties of the potential energy landscape

We develop a framework for understanding the difference between strong and fragile behavior in the dynamics of glass-forming liquids from the properties of the potential energy landscape. Our approach is based on a master equation description of the activated jump dynamics among the local minima of the potential energy (the so-called inherent structures) that characterize the potential energy landscape of the system. We study the dynamics of a small atomic cluster using this description as well as molecular dynamics simulations and demonstrate the usefulness of our approach for this system. Many of the remarkable features of the complex dynamics of glassy systems emerge from the activated dynamics in the potential energy landscape of the atomic cluster. The dynamics of the system exhibits typical characteristics of a strong supercooled liquid when the system is allowed to explore the full configuration space. This behavior arises because the dynamics is dominated by a few lowest-lying minima of the potential energy and the potential energy barriers between these minima. When the system is constrained to explore only a limited region of the potential energy landscape that excludes the basins of attraction of a few lowest-lying minima, the dynamics is found to exhibit the characteristics of a fragile liquid.

Monitoring of seasonal snow cover in Bhutan using remote sensing technique

All major rivers in Bhutan depend on snowmelt for discharge. Therefore, changes in snow cover due to climate change can influence distribution and availability of water. However, information about distribution of seasonal snow cover in Bhutan is not available. The MODIS snow product was used to study snow cover status and trends in Bhutan. Average snow cover area (SCA) of Bhutan estimated for the period 2002 to 2010 was 9030 sq. km, about 25.5% of the total land area. SCA trend of Bhutan for the period 2002-2010 was found to decrease (-3.27 +/- 1.28%). The average SCA for winter was 14,485 sq. km (37.7%), for spring 7411 sq. km (19.3%), for summer 4326 sq. km (11.2%), and for autumn 7788 sq. km (20.2%), mostly distributed in the elevation range 2500-6000 m amsl. Interannual and seasonal SCA trend both showed a decline, although it was not statistically significant for all sub-basins. Pho Chu sub-basin with 19.5% of the total average SCA had the highest average SCA. The rate of increase of SCA for every 100 m elevation was the highest (2.5%) in the Pa Chu sub-basin. The coefficient of variance of 1.27 indicates high variability of SCA in winter.

Simulating the daily discharge of the Mandovi River, west coast of India

A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June-September), with a peak during July-August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse rain-gauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system.

Si isotope variability in Proterozoic cherts

We report Si-isotopic compositions of 75 sedimentologically and petrographically characterized chert samples with ages ranging from similar to 2600 to 750 Ma using multi-collector inductively coupled plasma mass spectrometry. delta Si-30 values of the cherts analyzed in this study show a similar to 7 parts per thousand range, from -4.29 to +2.85. This variability can be explained in part by (1) simple mixing of silica derived from continental (higher delta Si-30) and hydrothermal (lower delta Si-30) sources, (2) multiple mechanisms of silica precipitation and (3) Rayleigh-type fractionations within pore waters of individual basins. We observe similar to 3 parts per thousand variation in peritidal cherts from a single Neoproterozoic sedimentary basin (Spitsbergen). This variation can be explained by Rayleigh-type fractionation during precipitation from silica-saturated porewaters. In some samples, post-dissolution and reprecipitation of silica could have added to this effect. Our data also indicate that peritidal cherts are enriched in the heavier isotopes of Si whereas basinal cherts associated with banded iron formations (BIF) show lower delta Si-30. This difference could partly be due to Si being derived from hydrothermal sources in BIFs. We postulate that the difference in delta Si-30 between non-BIF and BIF cherts is consistent with the contrasting genesis of these deposits. Low delta Si-30 in BIF is consistent with laboratory experiments showing that silica adsorbed onto Fe-hydroxide particles preferentially incorporates lighter Si isotopes. Despite large intrabasinal variation and environmental differences, the data show a clear pattern of secular variation. Low delta Si-30 in Archean cherts is consistent with a dominantly hydrothermal source of silica to the oceans at that time. The monotonically increasing delta Si-30 from 3.8 to 1.5 Ga appears to reflect a general increase in continental versus hydrothermal sources of Si in seawater, as well as the preferential removal of lighter Si isotopes during silica precipitation in iron-associated cherts from silica-saturated seawater. The highest delta Si-30 values are observed in 1.5 Ga peritidal cherts; in part, these enriched values could reflect increasing sequestration of light silica during soil-forming processes, thus, delivering relatively heavy dissolved silica to the oceans from continental sources. The causes behind the reversal in trend towards lower delta Si-30 in cherts younger than 1.5 Ga old are less clear. Cherts deposited 1800-1900 Ma are especially low delta Si-30, a possible indication of transiently strong hydrothermal input at this time. (C) 2012 Elsevier Ltd. All rights reserved.

Assessment of hydrologic impacts of climate change in Tunga-Bhadra river basin, India with HEC-HMS and SDSM

Climate change would significantly affect many hydrologic systems, which in turn would affect the water availability, runoff, and the flow in rivers. This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the TungaBhadra River, upstream of the Tungabhadra dam. The Hydrologic Engineering Center's Hydrologic Modeling System version 3.4 (HEC-HMS 3.4) is used for the hydrological modelling of the study area. Linear-regression-based Statistical DownScaling Model version 4.2 (SDSM 4.2) is used to downscale the daily maximum and minimum temperature, and daily precipitation in the four sub-basins of the study area. The large-scale climate variables for the A2 and B2 scenarios obtained from the Hadley Centre Coupled Model version 3 are used. After model calibration and testing of the downscaling procedure, the hydrological model is run for the three future periods: 20112040, 20412070, and 20712099. The impacts of climate change on the basin hydrology are assessed by comparing the present and future streamflow and the evapotranspiration estimates. Results of the water balance study suggest increasing precipitation and runoff and decreasing actual evapotranspiration losses over the sub-basins in the study area.

Formulation of a mathematical approach to regional frequency analysis

Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

Study of dynamic behaviour of recession curves

Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

Surface freshwater storage and variability in the Amazon basin from multi-satellite observations, 1993-2007

The amount of water stored and moving through the surface water bodies of large river basins (river, floodplains, wetlands) plays a major role in the global water and biochemical cycles and is a critical parameter for water resources management. However, the spatiotemporal variations of these freshwater reservoirs are still widely unknown at the global scale. Here, we propose a hypsographic curve approach to estimate surface freshwater storage variations over the Amazon basin combining surface water extent from a multi-satellite-technique with topographic data from the Global Digital Elevation Model (GDEM) from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Monthly surface water storage variations for 1993-2007 are presented, showing a strong seasonal and interannual variability, and are evaluated against in situ river discharge and precipitation. The basin-scale mean annual amplitude of similar to 1200 km(3) is in the range of previous estimates and contributes to about half of the Gravity Recovery And Climate Experiment (GRACE) total water storage variations. For the first time, we map the surface water volume anomaly during the extreme droughts of 1997 (October-November) and 2005 (September-October) and found that during these dry events the water stored in the river and floodplains of the Amazon basin was, respectively, similar to 230 (similar to 40%) and 210 (similar to 50%) km(3) below the 1993-2007 average. This new 15 year data set of surface water volume represents an unprecedented source of information for future hydrological or climate modeling of the Amazon. It is also a first step toward the development of such database at the global scale.

`Universal' recession curves and their geomorphological interpretation

The study of recession flows offers fundamental insights into basin hydrological processes and, in particular, into the collective behavior of the governing dominant subsurface flows and properties. We use here an existing geomorphological interpretation of recession dynamics, which links the exponent in the classic recession curve -dQ/dt - kQ(alpha) to the geometric properties of the time-varying drainage network to study the general properties of recession curves across a wide variety of river basins. In particular, we show how the parameter k depends on the initial soil moisture state of the basin and can be made to explicitly depend on an index discharge, representative of initial sub-subsurface storage. Through this framework we obtain a non-dimensional, event-independent, recession curve. We subsequently quantify the variability of k across different basins on the basis of their geometry, and, by rescaling, collapse curves from different events and basins to obtain a generalized, or `universal', recession curve. Finally, we analyze the resulting normalized recession curves and explain their universal characteristics, lending further support to the notion that the statistical properties of observed recession curves bear the signature of the geomorphological structure of the networks producing them. (C) 2014 Elsevier Ltd. All rights reserved.

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.

A Kaluza-Klein subtractor

We generalize the results of arXiv : 1212.1875 and arXiv : 1212.6919 on attraction basins and their boundaries to the case of a specific class of rotating black holes,namely the ergo-free branch of extremal black holes in Kaluza-Klein theory. We find that exact solutions that span the attraction basin can be found even in the rotating case by appealing to certain symmetries of the equations of motion. They are characterized by two asymptotic parameters that generalize those of the non-rotating case, and the boundaries of the basin are spinning versions of the (generalized) subtractor geometry. We also give examples to illustrate that the shape of the attraction basin can drastically change depending on the theory.

Ranking of global climate models for India using multicriterion analysis

Eleven GCMs (BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1) were evaluated for India (covering 73 grid points of 2.5 degrees x 2.5 degrees) for the climate variable `precipitation rate' using 5 performance indicators. Performance indicators used were the correlation coefficient, normalised root mean square error, absolute normalised mean bias error, average absolute relative error and skill score. We used a nested bias correction methodology to remove the systematic biases in GCM simulations. The Entropy method was employed to obtain weights of these 5 indicators. Ranks of the 11 GCMs were obtained through a multicriterion decision-making outranking method, PROMETHEE-2 (Preference Ranking Organisation Method of Enrichment Evaluation). An equal weight scenario (assigning 0.2 weight for each indicator) was also used to rank the GCMs. An effort was also made to rank GCMs for 4 river basins (Godavari, Krishna, Mahanadi and Cauvery) in peninsular India. The upper Malaprabha catchment in Karnataka, India, was chosen to demonstrate the Entropy and PROMETHEE-2 methods. The Spearman rank correlation coefficient was employed to assess the association between the ranking patterns. Our results suggest that the ensemble of GFDL2.0, MIROC3, BCCR-BCCM2.0, UKMO-HADCM3, MPIECHAM4 and UKMO-HADGEM1 is suitable for India. The methodology proposed can be extended to rank GCMs for any selected region.

Evaluation of TRMM PR Sampling Error Over a Subtropical Basin Using Bootstrap Technique

Quantitative use of satellite-derived rainfall products for various scientific applications often requires them to be accompanied with an error estimate. Rainfall estimates inferred from low earth orbiting satellites like the Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of nonnegligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. The authors investigate sampling uncertainty of seasonal rainfall estimates from the active sensor of TRMM, namely, Precipitation Radar (PR), based on 11 years of PR 2A25 data product over the Indian subcontinent. In this paper, a statistical bootstrap technique is investigated to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space-time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall were found to exhibit seasonal variations. To give a practical example of the implications of the bootstrap technique, PR relative sampling errors over a subtropical river basin of Mahanadi, India, are examined. Results reveal that the bootstrap technique incurs relative sampling errors < 33% (for the 2 degrees grid), < 36% (for the 1 degrees grid), < 45% (for the 0.5 degrees grid), and < 57% (for the 0.25 degrees grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. The study compares resulting error estimates to those obtained from latin hypercube sampling. Based on this study, the authors conclude that the bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in situ validation data. This technique has wider implications for decision making before incorporating microwave orbital data products in basin-scale hydrologic modeling.