Characteristics of spectral aerosol optical depths over India during ICARB

Spectral aerosol optical depth (AOD) measurements, carried out regularly from a network of observatories spread over the Indian mainland and adjoining islands in the Bay of Bengal and Arabian Sea, are used to examine the spatio-temporal and spectral variations during the period of ICARB (March to May 2006). The AODs and the derived Ångström parameters showed considerable variations across India during the above period. While at the southern peninsular stations the AODs decreased towards May after a peak in April, in the north Indian regions they increased continuously from March to May. The Ångström coefficients suggested enhanced coarse mode loading in the north Indian regions, compared to southern India. Nevertheless, as months progressed from March to May, the dominance of coarse mode aerosols increased in the columnar aerosol size spectrum over the entire Indian mainland, maintaining the regional distinctiveness. Compared to the above, the island stations showed considerably low AODs, so too the northeastern station Dibrugarh, indicating the prevalence of cleaner environment. Long-range transport of aerosols from tshe adjoining regions leads to remarkable changes in the magnitude of the AODs and their wavelength dependencies during March to May. HYSPLIT back-trajectory analysis shows that enhanced long-range transport of aerosols, particularly from the west Asia and northwest coastal India, contributed significantly to the enhancement of AOD and in the flattening of the spectra over entire regions; if it is the peninsular regions and the island Minicoy are more impacted in April, the north Indian regions including the Indo Gangetic Plain get affected the most during May, with the AODs soaring as high as 1.0 at 500 nm. Over the islands, the Ångström exponent (α) remained significantly lower (～1) over the Arabian Sea compared to Bay of Bengal (BoB) (～1.4) as revealed by the data respectively from Minicoy and Port Blair. Occurrences of higher values of α, showing dominance of accumulation mode aerosols, over BoB are associated well with the advection, above the boundary layer, of fine particles from the east Asian region during March and April. The change in the airmass to marine in May results in a rapid decrease in α over the BoB.     

Dynamic responses of atmospheric carbon dioxide concentration to global temperature changes between 1850 and 2010

Changes in Earth's temperature have significant impacts on the global carbon cycle that vary at different time scales, yet to quantify such impacts with a simple scheme is traditionally deemed difficult. Here, we show that, by incorporating a temperature sensitivity parameter(1.64 ppm yr~(-1) ?C~(-1)) into a simple linear carbon-cycle model, we can accurately characterize the dynamic responses of atmospheric carbon dioxide(CO_2) concentration to anthropogenic carbon emissions and global temperature changes between 1850 and 2010(r~2 0.96 and the root-mean-square error 1 ppm for the period from 1960onward). Analytical analysis also indicates that the multiplication of the parameter with the response time of the atmospheric carbon reservoir(～12 year) approximates the long-term temperature sensitivity of global atmospheric CO_2concentration(～15 ppm?C~(-1)), generally consistent with previous estimates based on reconstructed CO_2 and climate records over the Little Ice Age. Our results suggest that recent increases in global surface temperatures, which accelerate the release of carbon from the surface reservoirs into the atmosphere, have partially offset surface carbon uptakes enhanced by the elevated atmospheric CO_2 concentration and slowed the net rate of atmospheric CO_2 sequestration by global land and oceans by ～30%since the 1960 s. The linear modeling framework outlined in this paper thus provides a useful tool to diagnose the observed atmospheric CO_2 dynamics and monitor their future changes.     

The Gaojiacun Mafic-Ultramafic Complex （Sichuan, SW China）：Neoproterozoic Magmatic Activity at the Western Margin of the Yangtze Craton

1 Introduction The Gaojiacun intrusive complex is one of the numerous ultramafic-mafic intrusions in Sichuan Province of China. It was mapped during the 1970s and studied mainly by Chinese scientists (e.g. Geological Team 106, 1975; Shen et al., 1986, 1989; CGGJC, 1986; Yang et al., 1993; Li et al., 1995; Shen et al., 2003; Zhu et al., 2004a). Since the year 2000, China has become one of the largest PGE consumers. While the country can produce only less than 1 ton PGE/year, the Chin…     

Impact of Doppler weather radar data on thunderstorm simulation during STORM pilot phase—2009

This study assesses the impact of Doppler weather radar (DWR) data (reflectivity and radial wind) assimilation on the simulation of severe thunderstorms (STS) events over the Indian monsoon region. Two different events that occurred during the Severe Thunderstorms Observations and Regional Modeling (STORM) pilot phase in 2009 were simulated. Numerical experiments—3DV (assimilation of DWR observations) and CNTL (without data assimilation)—were conducted using the three-dimensional variational data assimilation technique with the Advanced Research Weather Research and Forecasting model (WRF-ARW). The results show that consistent with prior studies the 3DV experiment, initialized by assimilation of DWR observations, performed better than the CNTL experiment over the Indian region. The enhanced performance was a result of improved representation and simulation of wind and moisture fields in the boundary layer at the initial time in the model. Assimilating DWR data caused higher moisture incursion and increased instability, which led to stronger convective activity in the simulations. Overall, the dynamic and thermodynamic features of the two thunderstorms were consistently better simulated after ingesting DWR data, as compared to the CNTL simulation. In the 3DV experiment, higher instability was observed in the analyses of thermodynamic indices and equivalent potential temperature (θ _e) fields. Maximum convergence during the mature stage was also noted, consistent with maximum vertical velocities in the assimilation experiment (3DV). In addition, simulated hydrometeor (water vapor mixing ratio, cloud water mixing ratio, and rain water mixing ratio) structures improved with the 3DV experiment, compared to that of CNTL. From the higher equitable threat scores, it is evident that the assimilation of DWR data enhanced the skill in rainfall prediction associated with the STS over the Indian monsoon region. These results add to the body of evidence now which provide consistent and notable improvements in the mesoscale model results over the Indian monsoon region after assimilating DWR fields.     

An intercomparison of observational precipitation data sets over Northwest India during winter

Development of downscaling models for each calendar month using the data of predictors specifically selected for each calendar month may assists in better capturing the time-varying nature of the predictor-predictand relationships. Such approach will not allow the explicit modelling of the persistence of the predictand (e.g. lag-1 correlation). However, downscaling at an annual time step and subsequent disaggregation to monthly values can explicitly consider the modelling of the persistence of the predictand. This study investigated the potential of annual downscaling of a predictand and subsequent disaggregation of annual values to monthly values, in comparison to the potential of downscaling models separately developed for each calendar month. In the case study, annual and monthly downscaling models were developed for precipitation and evaporation at two stations located in Victoria, Australia. The output of the annual downscaling models was then disaggregated into monthly values using four different methods based on the method of fragments. It was found that the annual to monthly disaggregation methods and monthly downscaling models are able to reproduce the average of monthly observations with relatively higher accuracy in comparison to their ability in reproducing standard deviation, skewness and lag-1 serial correlation. Downscaling models separately developed for each calendar month were able to show relatively smaller root mean square errors for their time series indicating better overall agreement with observations in comparison to their counterpart annual to monthly disaggregation methods. Furthermore, it was found that not only the bias in the output of an annual downscaling model but also the presence of annual totals in the records of observations of a predictand that are very similar in magnitude, but having significantly different sets of fragments, can largely contribute to the poor performance of an annual to monthly disaggregation method.     

Metamodel-based design of alluvial channels at incipient motion subjected to seepage

Abstract

The design of an alluvial channel affected by seepage requires information about five basic parameters: particle size, water depth, energy slope, seepage velocity, and average velocity. The conventional approach to predicting the incipient motion in an alluvial channel cannot be applied in the case of a channel affected by seepage. Metamodelling techniques are nowadays widely used in engineering design to simulate a complex system. Here, a metamodel is described which employs the radial-basis function (RBF) network to predict the seepage velocity and energy slope based on experimental data under incipient motion conditions. It was found that the model fits experimental data very well and provides predictions for the design. With the help of the metamodel generated by the RBF network, design curves based on the RBF metamodel are presented for use in designing an alluvial channel when it is affected by seepage.

Citation Kumar, B., Sreenivasulu, G. & Ramakrishna Rao, A. (2010) Metamodel-based design of alluvial channels at incipient motion subjected to seepage. Hydrol. Sci. J. 55(3), 459–466.     

Microcosm experiments on the effect of nutrient enrichment and a soil layer on the development of freshwater plankton

We investigated the response of phytoplankton and zooplankton to experimental alteration of nitrate and phosphate levels in outdoor enclosures. Experiments were conducted in summer and winter and in the absence and presence of a layer of soil. The tubs (12 in all) except the two plain water controls were manured initially with a mixture of fresh cowdung (50g 1⁻¹), mustard oil cake (25 g l⁻¹) and poultry wastes (25 g l⁻¹; mostly excreta), prior to enrichment. Water samples were collected from the experimental tubs twice a week to measure selected physico-chemical and biological variables. Water temperature in the summer experiments ranged from 20–30 °C and during the winter experiments from 11–15 °C. The pH values ranged from 8.0 to 9.5 and the dissolved oxygen levels from 8.2–10.0 mg l⁻¹. The levels of soluble reactive phosphorus and nitrate nitrogen ranged from undetectable levels to 1800 μg l⁻¹ and 6000 μg l⁻¹, respectively. The increase in chlorophyll-a following enrichment was rapid (3–7 days) during summer, but slower in winter (7–14 days). The predominant phytoplankton species observed in the tubs belong to the genera Sphaerocystis, Chlorella, Scenedesmus, Cosmarium, Ulothrix, Zygnema, Gonium and Pandorina. The rotifer species observed were Brachionus calyciflorus, Rotaria neptunia, Lecane bulla, L. luna, L. unguitata, Euchlanis dilatata, Asplanchna intermedia, Pseudoharringia spp., Eosphora spp., Lepadella ovalis, Epiphanes brachionus, Hexarthra mira and Cephalodella gibba. The cladocerans observed were Macrothrix spp. and Alona spp.     

Scanning sky monitor (SSM) onboard AstroSat

Scanning Sky Monitor (SSM) onboard AstroSat is an Xray sky monitor in the soft X-ray band designed with a large field of view to detect and locate transient X-ray sources and alert the astronomical community about interesting phenomena in the X-ray sky. SSM comprises position sensitive proportional counters with 1D coded mask for imaging. There are three detector units mounted on a platform capable of rotation which helps covering about 50% of the sky in one full rotation. This paper discusses the elaborate details of the instrument and few immediate results from the instrument after launch.     

Climate variability, vegetation productivity and people at risk

Human domination of ecosystems has been pervasive over the last century, with nearly half of Earth's surface transformed by human actions. It is widely accepted that humans appropriate up to 50% of global net primary production (NPP), the energy base of all the trophic levels on the land surface. Yet, despite the important role of vegetation productivity for defining Earth habitability, the covariation of NPP and human population distribution has not been analyzed in depth. We used recently available satellite-based NPP estimates, along with gridded population at 0.5° resolution, first, to identify the global distribution of human population with reference to average NPP and to the various climatic constraints (temperature, water and cloud cover) that limit NPP, second, to analyze recent trends in global NPP in relation to population trends, and third, to identify populations that are vulnerable to changes in NPP due to interannual variability in climate. Our results indicate that over half of the global human population is presently living in areas with above the average NPP of 490 g C m⁻² year⁻¹. By 1998, nearly 56% of global population lived in regions where water availability strongly influences NPP. Per capita NPP declined over much of Africa between 1982 and 1998, in spite of the estimated increases in NPP over the same period. On average, NPP over 40% of the total vegetated land surface has shown significant correlations with ENSO-induced climate variability affecting over 2.8 billion people.