Outlier identification and correction for GRACE aggregated data

Gravity measurements within the Gravity Recovery and Climate Experiment (GRACE) provide a direct measure of monthly changes in mass over the Earth’s land masses. As such changes in mass mainly correspond to water storage changes, these measurements allow to close the continental water balance on large spatial scales and on a monthly time scale within the respective error bounds. When quantifying uncertainties, positive and negative peaks are detected in GRACE aggregated monthly time series (from different data providers) that do not correspond to hydrological or hydro-meteorological signals. These peaks must be interpreted as outliers, which carry the danger of signal degradation. In this paper an algorithm is developed to identify outliers and replace them with hydrologically plausible values. The algorithm is based on a statistical approach in which hydrological and hydro-meteorological signals are used to control the algorithm. The procedure of outlier detection is verified by evaluating catchment based aggregated GRACE monthly signals with ground truth from hydrology and hydro-meteorological signals. The results show improvement in the correlation of GRACE versus hydrometeorological and hydrological signals in most catchments. Also, the noise level is significantly reduced over 255 largest catchments.     

Use of daily precipitation uncertainties in streamflow simulation and forecast

Among other sources of uncertainties in hydrologic modeling, input uncertainty due to a sparse station network was tested. The authors tested impact of uncertainty in daily precipitation on streamflow forecasts. In order to test the impact, a distributed hydrologic model (PRMS, Precipitation Runoff Modeling System) was used in two hydrologically different basins (Animas basin at Durango, Colorado and Alapaha basin at Statenville, Georgia) to generate ensemble streamflows. The uncertainty in model inputs was characterized using ensembles of daily precipitation, which were designed to preserve spatial and temporal correlations in the precipitation observations. Generated ensemble flows in the two test basins clearly showed fundamental differences in the impact of input uncertainty. The flow ensemble showed wider range in Alapaha basin than the Animas basin. The wider range of streamflow ensembles in Alapaha basin was caused by both greater spatial variance in precipitation and shorter time lags between rainfall and runoff in this rainfall dominated basin. This ensemble streamflow generation framework was also applied to demonstrate example forecasts that could improve traditional ESP (Ensemble Streamflow Prediction) method.     

Early In-orbit Performance of Scanning Sky Monitor Onboard AstroSat

We report the in-orbit performance of Scanning Sky Monitor (SSM) onboard AstroSat. The SSM operates in the energy range 2.5 to 10 keV and scans the sky to detect and locate transient X-ray sources. This information of any interesting phenomenon in the X-ray sky as observed by SSM is provided to the astronomical community for follow-up observations. Following the launch of AstroSat on 28th September, 2015, SSM was commissioned on October 12th, 2015. The first power ON of the instrument was with the standard X-ray source, Crab in the field-of-view. The first orbit data revealed the basic expected performance of one of the detectors of SSM, SSM1. Following this in the subsequent orbits, the other detectors were also powered ON to find them perform in good health. Quick checks of the data from the first few orbits revealed that the instrument performed with the expected angular resolution of 12’ \(\times \) 2.5\(^\circ \) and effective area in the energy range of interest. This paper discusses the instrument aspects along with few on-board results immediately after power ON.     

Earth system curator: metadata infrastructure for climate modeling

The Earth System Curator is a National Science Foundation sponsored project developing a metadata formalism for describing the digital resources used in climate simulations. The primary motivating observation of the project is that a simulation/model’s source code plus the configuration parameters required for a model run are a compact representation of the dataset generated when the model is executed. The end goal of the project is a convergence of models and data where both resources are accessed uniformly from a single registry. In this paper we review the current metadata landscape of the climate modeling community, present our work on developing a metadata formalism for describing climate models, and reflect on technical challenges we have faced that require new research in the area of Earth Science Informatics.     

Tsunami Wave Interaction with Data Buoys

To plan for proper mitigation measures, one should have an advanced knowledge of the phenomenon of tsunami propagation from the deep ocean to coastal waters. There are a few methods to predict tsunamis in the ocean waters; one method is the effective use of data buoy measurements. Although data buoys have been used along the Indian waters there has been a tremendous growth in the number of buoy deployment recently. Under the National Data Buoy Programme (NDBP) of India, the 2.2 m diameter discus data buoys were deployed along the east and west coasts of India for measuring meteorological and ocean parameters. It would be advantageous if these buoys could be efficiently used to measure rare events such as tsunamis. Understanding the dynamic behavior of the buoy is of prime importance if a tsunami warning system is to be successful. This may be accomplished through experimental or numerical studies. A comprehensive experimental study has been conducted to understand the dynamic behavior of a wave rider buoy exposed to a variety of waves. It is common that tsunami waves are represented in terms of shallow water waves, namely solitary and cnoidal waves. Hence, in the present study, the discus type data buoy is scale modeled and tested under the action of solitary and cnoidal waves in the laboratory. The time histories of wave elevations, as well as heave and pitch motions of the buoy model, were analyzed through a spectral approach as well as through wavelet transformations. The wavelet approach gives more detailed insight into the spectral characteristics of the buoy motion in the time scale. The harmonic analyses were performed for the cnoidal wave elevations and subsequent motion characteristics that give an insight into the energy variations. The details of the model, instrumentation, testing conditions and the results are presented in this paper.     

Geo spatial variation of dengue risk zone in Madurai city using autocorrelation techniques

GeoJournal - Dengue is a microorganism sickness transmitted by the yellow-fever (mosquito Aedes aegypti) mosquito. The global incidence of dengue has grown dramatically in recent decades. In...     

A polarized microwave radiative transfer model for passive remote sensing

The objective of the present work is to develop a general purpose, polarized, microwave radiative transfer forward model, including calculation of interaction parameters for fast, simultaneous and accurate generation of radiances, for use in a wide variety of atmospheric retrieval applications. This complete polarized model includes the generation of atmospheric profiles, calculation of the interaction parameters and the solution of the vector radiative transfer equations. In the present work, the doubling and adding method is used to calculate radiances. Mie theory is used for spherical particles to evaluate the polarized scattering matrix. Two types of sea surface models applicable for specular and diffuse surfaces respectively are implemented. The model has been validated against standard benchmark cases and experimental data available in literature. While the model is itself generic, parametric studies are performed to study the influence of the vertical structure of the atmosphere, for two polarizations and a set of frequencies to be used on the microwave imager aboard the proposed Indo-French climate research satellite MEGHA-TROPIQUES.     

Evaluation of kernel density estimation methods for daily precipitation resampling

Kernel density estimators are useful building blocks for empirical statistical modeling of precipitation and other hydroclimatic variables. Data driven estimates of the marginal probability density function of these variables (which may have discrete or continuous arguments) provide a useful basis for Monte Carlo resampling and are also useful for posing and testing hypotheses (e.g bimodality) as to the frequency distributions of the variable. In this paper, some issues related to the selection and design of univariate kernel density estimators are reviewed. Some strategies for bandwidth and kernel selection are discussed in an applied context and recommendations for parameter selection are offered. This paper complements the nonparametric wet/dry spell resampling methodology presented in Lall et al. (1996).     

Landslide susceptibility mapping in a hilly terrain using remote sensing and GIS

Remote sensing and Geographic Information System (GIS) are well suited to landslide studies. The aim of this study is to prepare a landslide susceptibility map of a part of Ooty region, Tamil Nadu, India, where landslides are common. The area of the coverage is approximately 10 × 14 km in a hilly region where planting tea, vegetables and cash crops are in practice. Hence, deforestation, formation of new settlements and changing land use practices are always in progress. Land use and land cover maps are prepared from Indian Remote Sensing Satellite (IRS 1C - LISS III) imagery. Digital Elevation Model (DEM) was developed using 20 m interval contours, available in the topographic map. Field studies such as local enquiry, land use verification, landslide location identification were carried out. Analysis was carried out with GIS software by assigning rank and weights for each input data. The output shows the possible landslide areas, which are grouped for preparation of landslide susceptibility maps.