In this study, Gangotri glacier was monitored using Indian Remote Sensing (IRS) LISS-III sensor data in combination with field collected snow-meteorological data for a period of seven years (2001–2008). An overall decreasing trend in the areal extent of seasonal snow cover area (SCA) was observed. An upward shifting trend of wet snow line was observed in the beginning of melt period, i.e., in May and dominant wet snow conditions were observed between May and October. Snow meteorological parameters collected in the Gangotri sub-basin suggest reduction in fresh snowfall amount during winter, increase in rainfall amount during summer, decrease in snowfall days, increase in rainfall days and rising trend of average temperature. The prevailing wet snow condition on glacier has caused scouring of slopes which led the excessive soil/debris deposition on the glacier surface. This was observed as one of the major factor for activating fast melting and affecting the glacier health significantly. Apart from climatic conditions, terrain factors were observed for changing the glacio-morphology. The significant changes on the glacier surface were observed in the regions of abrupt slope change. The above factors affecting the Gangotri glacier health were also validated using high resolution satellite imageries and field visit. A deglaciation of 6% in overall area of Gangotri glacier was observed between the years 1962 and 2006.

Aerosol forcing remains a dominant uncertainty in climate studies. The impact of aerosol direct radiative forcing on Indian monsoon is extremely complex and is strongly dependent on the model, aerosol distribution and characteristics specified in the model, modelling strategy employed as well as on spatial and temporal scales. The present study investigates (i) the aerosol direct radiative forcing impact on mean Indian summer monsoon when a combination of quasi-realistic mean annual cycles of scattering and absorbing aerosols derived from an aerosol transport model constrained with satellite observed Aerosol Optical Depth (AOD) is prescribed, (ii) the dominant feedback mechanism behind the simulated impact of all-aerosol direct radiative forcing on monsoon and (iii) the relative impacts of absorbing and scattering aerosols on mean Indian summer monsoon. We have used CAM3, an atmospheric GCM (AGCM) that has a comprehensive treatment of the aerosol–radiation interaction. This AGCM has been used to perform climate simulations with three different representations of aerosol direct radiative forcing due to the total, scattering aerosols and black carbon aerosols. We have also conducted experiments without any aerosol forcing. Aerosol direct impact due to scattering aerosols causes significant reduction in summer monsoon precipitation over India with a tendency for southward shift of Tropical Convergence Zones (TCZs) over the Indian region. Aerosol forcing reduces surface solar absorption over the primary rainbelt region of India and reduces the surface and lower tropospheric temperatures. Concurrent warming of the lower atmosphere over the warm oceanic region in the south reduces the land–ocean temperature contrast and weakens the monsoon overturning circulation and the advection of moisture into the landmass. This increases atmospheric convective stability, and decreases convection, clouds, precipitation and associated latent heat release. Our analysis reveals a defining negative moisture-advection feedback that acts as an internal damping mechanism spinning down the regional hydrological cycle and leading to significant circulation changes in response to external radiative forcing perturbations. When total aerosol loading (both absorbing and scattering aerosols) is prescribed, dust and black carbon aerosols are found to cause significant atmospheric heating over the monsoon region but the aerosol-induced weakening of meridional lower tropospheric temperature gradient (leading to weaker summer monsoon rainfall) more than offsets the increase in summer-time rainfall resulting from the atmospheric heating effect of absorbing aerosols, leading to a net decrease of summer monsoon rainfall. Further, we have carried out climate simulations with globally constant AODs and also with the constant AODs over the extended Indian region replaced by realistic AODs. Regional aerosol radiative forcing perturbations over the Indian region is found to have impact not only over the region of loading but over remote tropical regions as well. This warrants the need to prescribe realistic aerosol properties in strategic regions such as India in order to accurately assess the aerosol impact.

The first step in developing any algorithm to retrieve the atmospheric temperature and humidity parameters at various pressure levels is the simulation of the top of the atmosphere radiances that can be measured by the satellite. This study reports the results of radiative transfer simulations for the multichannel infrared sounder of the proposed Indian satellite INSAT-3D due to be launched shortly. Here, the widely used community software k Compressed Atmospheric Radiative Transfer Algorithm (kCARTA) is employed for performing the radiative transfer simulations. Though well established and benchmarked, kCARTA is a line-by-line solver and hence takes enormous computational time and effort for simulating the multispectral radiances for a given atmospheric scene. This necessitates the development of a much faster and at the same time, equally accurate RT model that can drive a real-time retrieval algorithm. In the present study, a fast radiative transfer model using neural networks is proposed to simulate radiances corresponding to the wavenumbers of INSAT-3D. Realistic atmospheric temperature and humidity profiles have been used for training the network. Spectral response functions of GOES-13, a satellite similar in construction, purpose and design and already in use are used. The fast RT model is able to simulate the radiances for 1200 profiles in 18 ms for a 15-channel GOES profile, with a correlation coefficient of over 99%. Finally, the robustness of the model is tested using additional synthetic profiles generated using empirical orthogonal functions (EOF).

Carbon dioxide, water vapour, air temperature and wind measurements at 10 Hz sampling rate were carried out over the coast of Arabian Sea, Goa (15°21′N, 73° 51′E) in India. These observations were collected, in association with the surface layer turbulent parameters for the Arabian Sea Monsoon Experiment (ARMEX). In the summer monsoon period, concentration of CO₂ was in the range of 550–790 mg m⁻³ whereas the water vapour was in the range of 17.5–24.5 g m⁻³. The Fast Fourier Transform (FFT) analysis has been performed on these observations to investigate the spectral behaviour of CO₂ and water vapour. The relation between CO₂ and water vapour on various atmospheric scales has been proposed. CO₂ and water vapour observations confirmed the existence of periodicities of large (11, 8 days), meso (5 days) and micrometeorological (20 min) scales.

Collocated measurements of the boundary layer evolution and surface ozone, made for the first time at a tropical rural site (Gadanki 13.5°N, 79.2°E, 375 m amsl) in India, are presented here. The boundary layer related observations were made utilizing a lower atmospheric wind profiler and surface ozone observations were made using a UV analyzer simultaneously in April month. Daytime average boundary layer height varied from 1.5 km (on a rainy day) to a maximum of 2.5 km (on a sunny day). Correlated day-to-day variability in the daytime boundary layer height and ozone mixing ratios is observed. Days of higher ozone mixing ratios are associated with the higher boundary layer height and vice versa. It is shown that higher height of the boundary layer can lead to the mixing of near surface air with the ozone rich air aloft, resulting in the observed enhancements in surface ozone. A chemical box model simulation indicates about 17% reduction in the daytime ozone levels during the conditions of suppressed PBL in comparison with those of higher PBL conditions. On a few occasions, substantially elevated ozone levels (as high as 90 ppbv) were observed during late evening hours, when photochemistry is not intense. These events are shown to be due to southwesterly wind with uplifting and northeasterly winds with downward motions bringing ozone rich air from nearby urban centers. This was further corroborated by backward trajectory simulations.

In this study, the sensitivity of numerical simulations of tropical cyclones to physics parameterizations is carried out with a view to determine the best set of physics options for prediction of cyclones originating in the north Indian Ocean. For this purpose, the tropical cyclone Jal has been simulated by the advanced (or state of science) mesoscale Weather Research and Forecasting (WRF) model on a desktop mini super computer CRAY CX1 with the available physics parameterizations. The model domain consists of one coarse and two nested domains. The resolution of the coarse domain is 90 km while the two nested domains have resolutions of 30 and 10 km, respectively. The results from the inner most domain have been considered for analyzing and comparing the results. Model simulation fields are compared with corresponding analysis or observation data. The track and intensity of simulated cyclone are compared with best track estimates provided by the Joint Typhoon Warning Centre (JTWC) data. Two sets of experiments are conducted to determine the best combination of physics schemes for track and intensity and it is seen that the best set of physics combination for track is not suitable for intensity prediction and the best combination for track prediction overpredicts the intensity of the cyclone. The sensitivity of the results to orography and level of nesting has also been studied. Simulations were also done for the cyclone Aila with (i) best set of physics and (ii) randomly selected physics schemes. The results of the Aila case show that the best set of physics schemes has more prediction skill than the randomly selected schemes in the case of track prediction. The cumulus (CPS), planetary boundary layer (PBL) and microphysics (MP) parameterization schemes have more impact on the track and intensity prediction skill than the other parameterizations employed in the mesoscale model.

This paper reports the evolution of rain drop size distribution (DSD) during bright band (BB) and no-BB (NBB) conditions of low intensity rainfall events as observed by a vertically pointing Micro Rain Radar (MRR) over Pune (18.58°N, 73.92°E), India. The BB is identified by enhanced radar reflectivity factor 𝑍 (dBZ) at the 0°C isotherm. The gradient of hydrometeor fall velocity is found to be a good indicator in identifying the melting layer when enhanced radar reflectivity at melting layer is not prominent. The storm structures as observed by the MRR are compared with CloudSat observations that provide evidence of ice hydrometeor at ∼−60°C with clear indication of BB at 0°C. Storm heights at warmer than 0°C are evident during NBB conditions from CloudSat. This suggests that warm rain processes are responsible for producing rain during NBB conditions. During BB conditions, bimodal DSDs below the melting layer are observed at lower altitudes. The DSDs of shallow warm precipitating systems of NBB conditions are monomodal at all the altitudes. Significantly, normalized DSDs are found to be bimodal for BB conditions, and monomodal for NBB conditions which confirm different dominant microphysical processes. It is found that the observed bimodal DSDs during BB conditions are mainly due to the collision, coalescence and break-up processes. During NBB conditions, number and size of large raindrops grow while reaching the ground without much breakup. The radar reflectivity and rainfall intensity 𝑅 ($mmh^{−1}$) relationship of the form 𝑍 = $aR^b$ are found out for BB and NBB conditions. Existing different microphysical processes lead to large coefficient in the $Z–R$ relationship with small exponent during BB conditions while during NBB conditions the coefficients are small with large exponents.

During winter months (December, January, February – DJF), the western Himalayas (WH) receive precipitation from eastward moving extratropical cyclones, called western disturbances (WDs) in Indian parlance. Winter precipitation–moisture convergence–evaporation (P–C–E) cycle is analyzed for a period of 22 years (1981–2002: 1980(D)–1981(J, F) to 2001(D)–2002(J, F)) with observed and modelled (RegCM3) climatological estimates over WH. Remarkable model skills have been observed in depicting the hydrological cycle over WH. Although precipitation biases exist, similar spatial precipitation with well marked two maxima is simulated by the model. As season advances, temporal distribution shows higher precipitation in simulation than the observed. However, P–C–E cycle shows similar peaks of moisture convergence and evaporation in daily climatologies though with varying maxima/minima. In the first half of winter, evaporation over WH is mainly driven by ground surface and 2 m air temperature. Lowest temperatures during mid-winter correspond to lowest evaporation to precipitation ratio as well.

This paper utilizes wind speed data measured at 3 and 10 m above water surface level using buoys at 10 stations in Ionian and Aegean Seas to understand the behaviour of wind and thereafter energy yield at these stations using 5 MW rated power offshore wind turbine. With wind power densities of 971 and 693 W/m² at 50 m above water surface level, Mykonos and Lesvos were found to be superb and outstanding windy sites with wind class of 7 and 6, respectively. Other locations like Athos, Santorini and Skyros with wind power density of more than 530 W/m² and wind class of 5 were found to be the excellent sites. Around 15–16% higher winds were observed at 10 m compared to that at 3 m. Lower values of wind speed were found during summer months and higher during winter time in most of the cases reported in the present work. Slightly decreasing (∼2% per year) linear trends were observed in annual mean wind speed at Lesvos and Santorini. These trends need to be verified with more data from buoys or from nearby onshore meteorological stations. At Athos and Mykonos, increasing linear trends were estimated. At all the stations the chosen wind turbine could produce energy for more than 70% of the time. The wind speed distribution was found to be well represented by Weibull parameters obtained using Maximum likelihood method compared to WAsP and Method of Moments.

A new method for the calibration of regional ionospheric delay based on uncombined precise point positioning (U-PPP) is proposed in this study. The performance of the new method was comparatively validated in terms of its accuracy and robustness with respect to the phase-smoothed pseudorange (PSP) method through two short-baseline experiments. Accuracy of the PPP-derived ionospheric delays was further assessed by interpolating them to a user station to perform single-frequency simulated kinematic PPP. Two 24-hr period datasets of four continuous operation reference system (CORS) stations were analyzed, collected during calm and disturbed ionospheric conditions, respectively. The single-frequency GPS observables from a user station, that were a-priori corrected by the interpolated ionospheric delays, were utilized to implement single-frequency PPP (SF-PPP). The results show that interpolation accuracy is better than 1 dm and, with the proposed method, is less affected by the ionospheric activity; meanwhile, positioning accuracy of SF-PPP was 4 ∼5 cm (horizontal) and better than 1 dm (vertical). For comparison, two reference SF-PPP solutions were also obtained, in which the ionospheric delays are eliminated either by forming semi-combination observations or by using global ionosphere maps (GIM) model values; in both cases the positioning accuracy was only 4 ∼7 dm (horizontal) and 1 m (vertical). These results provide a further demonstration of the performance of PPP-based regional ionospheric calibration in the parameter domain.

Principal Component Analysis (PCA) and image processing are used to determine Total Electron Content (TEC) anomalies in the F-layer of the ionosphere relating to Typhoon Nakri for 29 May, 2008 (UTC). PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00–14:00 UT on 29 May, 2008 when the wind was most intense. Results show that at a height of approximately 150–200 km the TEC anomaly is highly localized; however, it becomes more intense and widespread with height. Potential causes of these results are discussed with emphasis given to acoustic gravity waves caused by wind force.

Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)–Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road–rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.

Precise information of geoid undulations is essential for obtaining the orthometric heights from Global Positioning System (GPS) measurements over any region; apart from providing the information of subsurface density distribution. This paper presents computation of geoid undulations over a part of southern Indian region from terrestrial gravity and elevation data using remove–restore technique that involves spherical Fast Fourier Transform (FFT) to compute ‘Stokes’ coefficients. Computed geoid undulations are compared with geoid obtained from global geopotential models such as EGM2008 and EIGENGRACE02S and measured GPS-levelling records at 67 locations. Statistical analysis of comparison suggests that the computed gravimetric geoid model has a good match with the geoid determined from GPS-levelling with rms of 0.1 m whereas EGM2008 has 0.46 m. The differences of GPS-levelling with EGM2008 at majority of stations fall in the range of ± 0.5 m, which indicates that EGM2008 may be used for orthometric height determination with an accuracy of > 0.5 m in the south Indian region and offers a reasonably good transformation platform from ellipsoid to local datum. However, local determination of geoid is necessary for better accuracy of orthometric height from GPS. The gravimetric geoid calculated from the available gravity data shows considerable improvement to the global model and can be used to achieve orthometric height with an accuracy of 0.1 m.

Himalayan seismicity is related to continuing northward convergence of Indian plate against Eurasian plate. Earthquakes in this region are mainly caused due to release of elastic strain energy. The Himalayan region can be attributed to highly complex geodynamic process and therefore is best suited for multifractal seismicity analysis. Fractal analysis of earthquakes (mb ≥ 3.5) occurred during 1973–2008 led to the detection of a clustering pattern in the narrow time span. This clustering was identified in three windows of 50 events each having low spatial correlation fractal dimension ($D_C$) value 0.836, 0.946 and 0.285 which were mainly during the span of 1998 to 2005. This clustering may be considered as an indication of a highly stressed region. The Guttenberg Richter 𝑏-value was determined for the same subsets considered for the $D_C$ estimation. Based on the fractal clustering pattern of events, we conclude that the clustered events are indicative of a highly stressed region of weak zone from where the rupture propagation eventually may nucleate as a strong earthquake. Multifractal analysis gave some understanding of the heterogeneity of fractal structure of the seismicity and existence of complex interconnected structure of the Himalayan thrust systems. The present analysis indicates an impending strong earthquake, which might help in better hazard mitigation for the Kumaun Himalaya and its surrounding region.

To evaluate the conventional methods for mapping hydrothermal altered deposits by using Landsat 7 ETM+ image in and around Kuju volcano is the prime target of our study. The Kuju volcano is a mountainous composite which consists of hornblende-andesite lava domes and associated lava flows. We used the colour composite, band ratio, principal component analysis, least square fitting and reference spectra analysis methods. The colour composite and band ratio methods showed very clearly the hydrothermal altered deposits of clay minerals, iron oxides and ferric oxides around the fumaroles. The principal component analysis using the Crosta technique also enabled us to represent undoubtedly the altered hydroxyl and iron-oxide mineral deposits of this region concentrating around the fumaroles. Least square fitting method illustrated the goethite, hematite and clay alteration region. Finally the target detection method for reference spectral analysis by using ENVI 4.3 detected the representative hydrothermal altered minerals around Kuju volcano fumaroles area. Therefore, all the methods showed high efficiency for mapping hydrothermal altered deposits especially iron-oxide minerals such as hematite, goethite and jarosite, which are alteration products of hydrothermal sulfides around the fumaroles.

Soil contamination by heavy metals has been a major concern for last few decades due to increase in urbanization and industrialization. The main objective of this research was to identify the heavy metal contaminated zones in the study area. Twenty five soil samples collected throughout the agriculture, residential and industrial areas were analysed by X-ray Fluorescence Spectrometer (XRF) for trace metals and major oxides. These metals can affect the quality of soil and infiltrate through the soil, thereby causing groundwater pollution. Based on the chemical analysis of major oxides (SiO₂, Al₂O₃, Fe₂O₃, MnO, MgO, CaO, Na₂O, K₂O, TiO₂, and P₂O₅) and their distribution; it is observed that these soils are predominantly siliceous type with slight enrichment of alumina component in the study area. Correlation matrix (CM) and factor analysis (FA) is employed to the heavy metal variables, viz., Ba, Cr, Cu, Ni, Pb, Rb, Sr, V, Y, Zn and Zr of the soil to determine the dominant factors contributing to the soil contamination in the area. In the analysis, five factors emerged as significant contributors to the soil quality. The total contribution of these five factors is about 90%. The contribution of the first factor is about 45% and has significant positive loadings of Co, Cr, Cu, Ni and Zn. The contribution of second factor is 22% and has significant positive loadings of Rb, Sr and Y. The contribution of third, fourth and fifth factors is 10, 8 and 5% and show positive loadings for lead, molybdenum and barium respectively to the soil contamination. The spatial variation maps deciphering different zones of heavy metal concentration in the soil were generated in a GIS (geographic information system) based environment using ArcGIS 9.3.1. The results reveal that heavy metal contamination in the area is mainly due to anthropogenic activities.

In the study area, changes in the facies of sediments and spores-pollen content appear to be all causally linked with the depositional set-up. Here, the qualitative and quantitative changes observed in the spores-pollen assemblages have led to recognize 10 Assemblage-zones representing from that earliest Permian in the Talchir Formation to that latest Late Triassic in the Parsora Formation. These sporespollen assemblages are obtained from the wider parts in the Singrauli Gondwana Basin that includes (i) Moher sub-basin (boreholes SSM-1 and 2), and (ii) Singrauli main sub-basin (boreholes SMJS-2, 3 and SMBS-1). The progressively changing spores-pollen content infer the hiatuses of varied magnitude in the sedimentary sequences during the extended time interval of Permian and Triassic.

The climatic variability and the influence of temperature and sea level fluctuations on the earth’s surface configuration during the Holocene are being discussed all over the world. The present study evaluates the palaeo-environmental conditions of western coast of India during this epoch through the analysis of pollen grains embedded in a carbonaceous clay formation (≅ 0.4-0.6 m) found sandwiched within the palaeodeposit of sand of Meenachil River basin. The carbon dating revealed that the clay formation has an age of 5786 ± 94¹⁴C yr BP, while the embedded wood samples have the age varying in between 2888 ± 78 and 5780 ± 95¹⁴C yr BP. The overall analysis suggests that the southwestern margin of India had experienced high intensity rainfall during the earlier part of the Atlantic chronozone due to then strengthened Asiatic monsoon, while water stagnation and hydrological modifications were observed during the later part. The dominance of weeds and lesser number of tree elements suggested a drier climate during the end of the Atlantic period. Besides, the morphometric rearrangement of the Meenachil River contemporaneous to the geomorphological modifications of the southwestern coast of India shall be classified into three categories: (1) Pre-Vembanad Lake formation, (2) Contemporaneous to lake formation and (3) Post-Lake formation.