Wavelet-based combination approach for modeling sub-divisional rainfall in India

Agriculture in India is highly sensitive to climatic variations particularly to rainfall and temperature; therefore, any change in rainfall and temperature will influence crop yields. An understanding of the spatial and temporal distribution and changing patterns in climatic variables is important for planning and management of natural resources. Time series analysis of climate data can be a very valuable tool to investigate its variability pattern and, maybe, even to predict short- and long-term changes in the series. In this study, the sub-divisional rainfall data of India during the period 1871 to 2016 has been investigated. One of the widely used powerful nonparametric techniques namely wavelet analysis was used to decompose and de-noise the series into time–frequency component in order to study the local as well as global variation over different scales and time epochs. On the decomposed series, autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models were applied and by means of inverse wavelet transform, the prediction of rainfall for different sub-divisions was obtained. To this end, empirical comparison was carried out toward forecast performance of the approaches namely Wavelet-ANN, Wavelet-ARIMA, and ARIMA. It is reported that Wavelet-ANN and Wavelet-ARIMA approach outperforms the usual ARIMA model for forecasting of rainfall for the data under consideration.     

Combining climatological and participatory approaches for assessing changes in extreme climatic indices at regional scale

This paper combines the climatological and societal perspectives for assessing future climatic extremes over Kangasabati River basin in India using an ensemble of four high resolution (25 km) regional climate model (RCM) simulations from 1970 to 2050. The relevant extreme indices and their thresholds are defined in consultation with stakeholders and are then compared using RCM simulations. To evaluate the performance of RCM in realistically representing atmospheric processes in the basin, model simulations driven with ERAInterim global re-analysis data from 1989 to 2008 are compared with observations. The models perform well in simulating seasonality, interannual variability and climatic extremes. Future climatic extremes are evaluated based on RCM simulations driven by GCMs, for present (1970–1999) and for the SRES A1B scenario for future (2021–2050) period. The analysis shows an intensification of majority of extremes as projected by future ensemble mean. The study suggests that there is a marked consistency in stakeholder observed changes in climate extremes and future predicted trends.     

Theoretical studies on OH and Cl initiated hydrogen atom abstraction of HFE-227pc (CF3OCF2CHF2)

The kinetics of hydrogen atom abstraction reactions of HFE-227pc by OH and Cl was studied by ab initio method. The structural optimization and frequency calculation of the titled compound and the species formed during the abstraction reactions were performed with density functional theory using hybrid meta density functional MPWB1K with 6–31?+?G(d,p) basis set. The energy of the species was further refined by making a single point energy calculation at G3B3 level of theory. The standard enthalpies of formation of reactant and the radical formed after H-atom abstraction was calculated using isodesmic method. The rate constants of abstraction reactions were calculated using Conventional Transition State Theory (CTST) and were found to be 1.5?×?10^?15 and 0.53?×?10^?16 cm³molecule^?1 s^?1 for OH and Cl respectively. The calculated value for the abstraction by OH is close to the experimental value of 2.26?×?10^?15 cm³molecule^?1 s^?1 whereas the same for Cl is found to be about five times lower than that of 2.70?×?10^?16 cm³molecule^?1 s^?1. The theoretical studies yielded the enthalpies of formation and the rate constants that are vital in determining the lifetime of HFE-227pc.     

GPS-derived precipitable water vapour and its comparison with MODIS data for Almora, Central Himalaya, India

The present study is an attempt to analyse the precipitable water vapour (PWV) derived from Global Positioning System (GPS) and observed meteorological data over Almora, Central Himalayan Region. The PWV values derived using GPS study is compared with the corresponding moderate resolution imaging spectro-radiometer (MODIS) data. The statistical analysis reveals a positive correlation between both methods. Moderate resolution imaging spectroradiometer near-infrared (MODIS NIR) clear column water vapour product shows a higher correlation (R ² = 90–93 %) with GPS-derived precipitable water vapour on annual scale as compared to the seasonal scale (R ² = 62–87 %). MODIS is found to be overestimating in NIR clear column where the magnitude of bias and RMSE show systematic changes from season to season. Monsoon is an important phenomenon in the Indian weather context and holds significant importance in Central Himalayan ecosystem. The monthly and seasonal variation in precipitable water vapour is related with monsoon onset in the region. Diurnal variations in precipitable water vapour are studied with other meteorological data over Almora during dry and wet season. The precipitable water vapour had minimum value in the morning, increases in the afternoon to evening and again decreases to the midnight in both the dry and wet seasons. These results suggest that diurnal variation of water vapour is caused by the transport of water vapour by thermally induced local circulation.     

Comparison between urban aerosol products retrieved from collocated Cimel and Prede Sun/sky radiometers at Pune, India

To comprehend the characteristics of heterogeneous aerosols, apart from some thematic multi-institutional, multi-platform and multi-parameter campaigns conducted at several places over the globe, presently two major ground-based networks, involving Cimel (AERONET) and Prede (SKYNET) Sun/sky photometers/radiometers have been in progress. In this paper, we report the results of a study that has been undertaken to compare the performance and data products of Cimel and Prede instruments, which were operated concurrently for a period of about 2 years, at the Indian Institute of Tropical Meteorology, Pune, India. The results show a good agreement in the direct Sun observations (aerosol optical depth). The results are also substantiated by making comparison with surface-level black carbon aerosol mass concentration, apart from comparison of other parameters. With regard to the retrieved products such as aerosol size distribution, Prede shows more or less equal concentration of fine mode and relatively more concentration of coarse mode aerosol as compared to those measured by the Cimel. Moreover, the single scattering albedo values measured by the Prede overestimate those observed by the Cimel. These deviations are found to be primarily due to the nature of aerosol loading (turbidity) in the sensing region which is sensitive to the data retrieval techniques including model assumptions employed in both networks. The results of the present study are found useful for multidimensional mapping of aerosol characteristics by integrating the products from both AERONET and SKYNET monitoring stations and thereby help understanding better the impact of aerosols on climate.     

Characterizing atmospheric surface layer turbulence using chaotic return map analysis

Nonlinear time series analysis methods are used to investigate the dynamics of mechanical and convective turbulences in the atmospheric surface layer flow. Using dynamical invariant analysis (e.g. correlation dimension, Lyapunov exponent and mutual information) along with recurrence quantification analysis (e.g. recurrent rate, determinism, average diagonal length of recurrence plot, etc.) of the vertical wind component data, it is confirmed that a convective turbulence is a lower order manifold in its phase space exhibiting higher degree of organization than a mechanical turbulence. Applying a quasi-one-dimensional chaotic return map technique, the topological differences between the mechanical and convective turbulences are explored. These quasi-one-dimensional return maps are produced using the local maxima of the first principal component of the reconstructed turbulence data. A comparison of the probability distribution of the local maxima of a forced Lorenz model with the turbulence data indicates the possible existence of a stable fixed point for both type of turbulences. Furthermore, dynamically the mechanical turbulence is found to resemble an unforced Lorenz model whereas the convective turbulence resembles a forced Lorenz model.     

CFSv2 ensemble prediction of the wintertime Arctic Oscillation

Lagged ensembles from the operational Climate Forecast System version 2 (CFSv2) seasonal hindcast dataset are used to assess skill in forecasting interannual variability of the December–February Arctic Oscillation (AO). We find that a small but statistically significant portion of the interannual variance (>20 %) of the wintertime AO can be predicted at leads up to 2 months using lagged ensemble averages. As far as we are aware, this is the first study to demonstrate that an operational model has discernible skill in predicting AO variability on seasonal timescales. We find that the CFS forecast skill is slightly higher when a weighted ensemble is used that rewards forecast runs with the most accurate representations of October Eurasian snow cover extent (SCE), hinting that a stratospheric pathway linking October Eurasian SCE with the AO may be responsible for the model skill. However, further analysis reveals that the CFS is unable to capture many important aspects of this stratospheric mechanism. Model deficiencies identified include: (1) the CFS significantly underestimates the observed variance in October Eurasian SCE, (2) the CFS fails to translate surface pressure anomalies associated with SCE anomalies into vertically propagating waves, and (3) stratospheric AO patterns in the CFS fail to propagate downward through the tropopause to the surface. Thus, alternate boundary forcings are likely contributing to model skill. Improving model deficiencies identified in this study may lead to even more skillful predictions of wintertime AO variability in future versions of the CFS.     

Biosorption of Cd (Ⅱ) and Pb (Ⅱ) Ions by Aqueous Solutions of Novel Alkalophillic Streptomyces VITSVK5 spp. Biomass

Discharge of heavy metals from metal processing industries is known to have adverse effects on the environment. Biosorption of heavy metals by metabolically inactive biomass of microbial organisms is an innovative and alternative technology for removal of these pollutants from aqueous solution. The search of marine actinobacteria with potential heavy metal biosorption ability resulted in the identification of a novel alkalophilic Streptomyces VITSVK5 species. The biosorption property of Streptomyces VITSVK5 spp. was investigated by absorbing heavy metals Cadmium (Cd) and Lead (Pb). Physiochemical characteristics and trace metal concentration analysis of the backwater showed the concentrations of different metals were lead 13±2.1 μg L⁻¹, cadmium 3.1±0.3μg L⁻¹, zinc 8.4±2.6μg L⁻¹ and copper 0.3±0.1μg L⁻¹, whereas mercury was well below the detection limit. The effect of pH and biomass dosage on removal efficiency of heavy metal ions was also investigated. The optimum pH for maximal biosorption was 4.0 for Cd (II) and 5.0 for Pb (II) with 41% and 84% biosorption respectively. The biosorbent dosage was optimized as 3 g L-1 for both the trace metals. Fourier transform infrared absorption spectrum results indicated the chemical interactions of hydrogen atoms in carboxyl (-COOH), hydroxyl (-CHOH) and amine (-NH₂) groups of biomass with the metal ions. This could be mainly involved in the biosorption of Cd (II) and Pb (II) onto Streptomyces VITSVK5 spp. The results of our study revealed Streptomyces metabolites could be used to develop a biosorbent for adsorbing metal ions from aqueous environments.     

A class of well-behaved generalized charged analogues of Vaidya-Tikekar type fluid sphere in general relativity

In this paper first ever we have developed a class of well behaved charged fluid spheres expressed by a space time with its hypersurfaces $t = \operatorname {const}$ . as spheroid for the case 0<K<1 with surface density 2×10¹⁴ gm/cm³. The same utilized to construct a superdense star and seen that star satisfies all well behaved condition for 0<K≤0.038. The maximum mass occupied and the corresponding radius are found to be 4.830982M _Θ and 20.7612 km respectively. The redshift at the center and on the surface is given z ₀=0.425367 and z _a =0.240901.     

Changes in Quasi-periodic Variations of Solar Photospheric Fields: Precursor to the Deep Solar Minimum in Cycle 23?

Possible precursor signatures in the quasi-periodic variations of solar photospheric fields were investigated in the build-up to one of the deepest solar minima experienced in the past 100 years. This unusual and deep solar minimum occurred between Solar Cycles 23 and 24. We used both wavelet and Fourier analysis to study the changes in the quasi-periodic variations of solar photospheric fields. Photospheric fields were derived using ground-based synoptic magnetograms spanning the period 1975.14 to 2009.86 and covering Solar Cycles 21, 22, and 23. A hemispheric asymmetry in the periodicities of the photospheric fields was seen only at latitudes above ±?45^° when the data were divided into two parts based on a wavelet analysis: one prior to 1996 and the other after 1996. Furthermore, the hemispheric asymmetry was observed to be confined to the latitude range of 45^° to 60^°. This can be attributed to the variations in polar surges that primarily depend on both the emergence of surface magnetic flux and varying solar-surface flows. The observed asymmetry along with the fact that both solar fields above ±?45^° and micro-turbulence levels in the inner-heliosphere have been decreasing since the early- to mid-nineties (Janardhan et al. in Geophys. Res. Lett. 382, 20108, 2011) suggest that around this time active changes occurred in the solar dynamo that governs the underlying basic processes in the Sun. These changes in turn probably initiated the build-up to the very deep solar minimum at the end of Cycle 23. The decline in fields above ±?45^°, for well over a solar cycle, would imply that weak polar fields have been generated in the past two successive solar cycles, viz. Cycles 22 and 23. A continuation of this declining trend beyond 22 years, if it occurs, will have serious implications for our current understanding of the solar dynamo.