Search Results - "Anantharaj, Valentine G"
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A Baseline for Global Weather and Climate Simulations at 1 km Resolution
Published in Journal of advances in modeling earth systems (01-11-2020)“…In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four‐month…”
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Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama‐Coosa‐Tallapoosa River Basin
Published in Journal of geophysical research. Atmospheres (16-05-2017)“…Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has…”
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Impacts of land use-land cover change on climate and future research priorities
Published in Bulletin of the American Meteorological Society (2010)“…[...] we also need strategies that will help us to detect and overcome these biases and thus lead to an improved understanding of the role of land use forcing…”
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Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling
Published in Earth and space science (Hoboken, N.J.) (01-02-2021)“…This study integrates machine learning and particle‐resolved aerosol simulations to develop emulators that predict submicron aerosol mixing state indices from…”
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Optimally Merging Precipitation to Minimize Land Surface Modeling Errors
Published in Journal of applied meteorology and climatology (01-03-2010)“…This paper introduces a new method to improve land surface model skill by merging different available precipitation datasets, given that an accurate land…”
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On the Use of a Cluster Ensemble Cloud Classification Technique in Satellite Precipitation Estimation
Published in IEEE journal of selected topics in applied earth observations and remote sensing (01-10-2012)“…In this paper, the link-based cluster ensemble (LCE) method is utilized to improve cloud classification and satellite precipitation estimation. High resolution…”
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linear merging methodology for high-resolution precipitation products using spatiotemporal regression
Published in International journal of remote sensing (20-12-2012)“…Currently, the only viable option for a global precipitation product is the merger of several precipitation products from different modalities. In this…”
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On the Use of the Genetic Algorithm Filter-Based Feature Selection Technique for Satellite Precipitation Estimation
Published in IEEE geoscience and remote sensing letters (01-09-2012)“…A feature selection technique is used to enhance the precipitation estimation from remotely sensed imagery using an artificial neural network (PERSIANN) and…”
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Enhancement of Satellite Precipitation Estimation via Unsupervised Dimensionality Reduction
Published in IEEE transactions on geoscience and remote sensing (01-10-2012)“…A methodology to enhance satellite precipitation estimation using unsupervised dimensionality reduction (UDR) techniques is developed. This enhanced technique…”
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Precipitation data fusion using vector space transformation and artificial neural networks
Published in Pattern recognition letters (15-07-2010)“…We have developed a new methodology to fuse several precipitation datasets, available from different estimation techniques. The method is based on artificial…”
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Journal Article Conference Proceeding -
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Augmenting satellite precipitation estimation with lightning information
Published in International journal of remote sensing (2013)“…We have used lightning information to augment the precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification…”
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Comparison of satellite‐derived TOA shortwave clear‐sky fluxes to estimates from GCM simulations constrained by satellite observations of land surface characteristics
Published in International journal of climatology (15-11-2010)“…Clear‐sky, upwelling shortwave flux at the top of the atmosphere $\left(S_{\rm {TOA}}^{\uparrow}\right)$, simulated using the atmospheric and land model…”
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Wildfire Potential Mapping over the State of Mississippi: A Land Surface Modeling Approach
Published in GIScience and remote sensing (01-07-2012)“…A relationship between the likelihood of wildfires and various drought metrics (soil moisture-based fire potential indices) were examined over the southern…”
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Soil Moisture Sensitivity to NRL-Blend High-Resolution Precipitation Products: Analysis of Simulations With Two Land Surface Models
Published in IEEE journal of selected topics in applied earth observations and remote sensing (01-03-2010)“…We examine the Naval Research Laboratory (NRL) blended satellite (NRL-Blend) High-Resolution Precipitation Product (HRPP) as a proxy for a Global Precipitation…”
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A pattern recognition based approach to consistency analysis of geophysical datasets
Published in Computers & geosciences (01-04-2010)“…Remotely sensed data from satellites are often validated by comparing them against ground-based measurements which usually are relatively sparse. Conventional…”
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Interpolation of Missing Values in AMSR-E Soil Moisture Data Using Modified SSA
Published in IEEE geoscience and remote sensing letters (01-03-2011)“…Soil moisture data available from the Advanced Microwave Scanning Radiometer-Earth Observation System (AMSR-E) onboard the National Aeronautic and Space…”
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Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion
Published in Boundary - layer meteorology (01-12-2009)“…Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a…”
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Journal Article Conference Proceeding -
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An optimal merging technique for high‐resolution precipitation products
Published in Journal of advances in modeling earth systems (01-04-2011)“…Precipitation products are currently available from various sources at higher spatial and temporal resolution than any time in the past. Each of the…”
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Observed and Simulated Soil Moisture Variability over the Lower Mississippi Delta Region
Published in Journal of hydrometeorology (01-12-2008)“…To better understand error and spatial variability sources of soil moisture simulated with land surface models, observed and simulated values of soil moisture…”
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