Near-infrared detection of potential evidence for microscopic organisms on Europa

The possibility of an ocean within the icy shell of Jupiter's moon Europa has established that world as a primary candidate in the search for extraterrestrial life within our Solar System. This paper evaluates the potential to detect evidence for microbial life by comparing laboratory studies of terrestrial microorganisms with measurements from the Galileo Near Infrared Imaging Spectrometer (NIMS). If the interior of Europa at one time harbored life, some evidence may remain in the surface materials. Examination of laboratory spectra of terrestrial extremophiles measured at cryogenic temperatures reveals distorted, asymmetric nearinfrared absorption features due to water of hydration. The band centers, widths, and shapes of these features closely match those observed in the Europa spectra. These features are strongest in reddish-brown, disrupted terrains such as linea and chaos regions. Narrow spectral features due to amide bonds in the microbe proteins provide a means of constraining the abundances of such materials using the NIMS data. The NIMS data of disrupted terrains exhibit distorted, asymmetric near-infrared absorption features consistent with the presence of water ice, sulfuric acid octahydrate, hydrated salts, and possibly as much as 0.2 mg cm(-3) of carbonaceous material that could be of biological origin. However, inherent noise in the observations and limitations of spectral sampling must be taken into account when discussing these findings.     

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.     

Impact of four dimensional assimilation of satellite data on long-range simulations over the Indian region during monsoon 2006

A number of experiments were conducted to study the impact of updating model basic fields by satellite data (Quick Scatterometer (QSCAT) surface winds and Atmospheric Infrared Sounder (AIRS) temperature and humidity profiles) on long-range simulation during the Indian summer monsoon 2006. The Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model version5 (MM5) and its four dimensional data assimilation (FDDA) technique was used for the numerical simulations. The spatial distribution and temporal variation in model simulated basic meteorological parameters and rainfall were verified against the observed fields from National Center for Environmental Prediction (NCEP) analysis and Tropical Rainfall Measuring Mission (TRMM), respectively. The overall analysis of the results from QSCAT surface wind assimilation as compared to control simulation (CNT; without the satellite data assimilation) suggest that a better representation of a single level wind field during model integration fail to make significant improvement in the model simulation both in the basic meteorological parameters and rainfall. The assimilation of temperature and humidity profiles from the AIRS during model integration significantly improved the rainfall prediction during monsoon period. It is found that the improvement in rainfall prediction is attributed to improved thermodynamics structure due to AIRS profile assimilation and the degree of improvement is more in temperature prediction as compared to humidity prediction. It is also found that the prediction over the regions, such as south west part of India and foothills of Himalaya, where a complex orography exists, is not significantly benefited from satellite data assimilation which highlights the need of improvement in the model in addition to a better representation of atmospheric state.     

Precursory signature of several major earthquakes studied using 40 kHz low frequency signal

To investigate the precursory signature of earthquakes on low frequency (LF) signal propagation, six earthquakes, having magnitude greater than equal to 6.5 and depth less than equal to 30 km, are being studied. The base line level of 40 kHz signal, transmitted from JJY station, Japan, is analysed with respect to V_d statistical parameter. Results show that the V_d parameter values starts fluctuating from its ambient levels before and during the days of the earthquakes, with significant variation starting 1–3 days prior to the earthquake concerned. This present study is an approach for identifying the precursory signatures of earthquakes on LF signal propagation using a new methodology with V_d parameter.     

Plasma electron temperature variability in lunar surface potential and in electric field under average solar wind conditions

The Moon is immersed in plasma environment. The most interesting challenge of the lunar plasma– field environment is that it is alternatively dominated by the extended but variable outer atmosphere of the Earth – the magnetosphere – and by the extended but highly variable solar atmosphere – the solar wind. Understanding the plasma environment and its interaction with the lunar surface will be beneficial to both manned and robotic surface exploration activities and to scientific investigations. Presented is a preliminary map of variations of lunar surface electric potential over the day side and night side using probe equations and a discussion on dust dynamics in this E-field structure using the data from Electron Reflectometer in Lunar Prospector spacecraft during 1998–1999. On the day side, potential is around 5 V and on the night side it reaches up to −82 V. On the night side region, only highly energetic electrons can overcome this large negative potential. The variation at electron temperature (T_e) strongly reflects in the surface potential. The potential reaches to a value of −82 V for T_e = 58 eV. Surface charging causes the electrostatic transport of charged dust grains. Dust grain size of 0.1 μm shows a levitation height of 4.92 m on lunar day side, 748 m on terminator region and 3.7 km on the night side. The radius of maximum sized grain to be lofted, R_max, peaks at the terminator region (R_max = 0.83 μm). At the transition region dust levitation is almost absent. This region is most suited for exploration activities as the region is free from hazards caused by lunar dust.     

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.