Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Malarvizhi Arulraj"'
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-12 (2024)
Abstract Satellite-based Quantitative Precipitation Estimates (QPE) are indirect estimates of precipitation rates and as such are often prone to errors, warranting a need for characterizing the associated uncertainties before being used in applicatio
Externí odkaz:
https://doaj.org/article/61932cfb7f124db6bdc88260c485fe39
Autor:
Douglas Miller, Malarvizhi Arulraj, Ralph Ferraro, Christopher Grassotti, Bob Kuligowski, Shuyan Liu, Veljko Petkovic, Shaorong Wu, Pingping Xie
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2500 (2021)
Two heavy rainfall events occurring in early 2020 brought flooding, flash flooding, strong winds, and tornadoes to the southern Appalachian Mountains. Part I of the study examined large-scale atmospheric contributions to the atmospheric river-influen
Externí odkaz:
https://doaj.org/article/137f051bb7154edd81efcbfc043ac8b8
Publikováno v:
Environmental Research Letters, Vol 12, Iss 10, p 104005 (2017)
Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes o
Externí odkaz:
https://doaj.org/article/f00e6cd8812d4445a2ad2ae9fd34b0ff
Autor:
Ana P. Barros, Malarvizhi Arulraj
Ground-clutter is a major cause of large detection and underestimation errors in satellite-based (e.g. Global Precipitation Measurement Dual Polarization Radar, GPM DPR) precipitation radar retriev...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d5a011ddb04c2cf1bcb3caf57913567
https://doi.org/10.1002/essoar.10502701.1
https://doi.org/10.1002/essoar.10502701.1
Autor:
Ana P. Barros, Malarvizhi Arulraj
Publikováno v:
Advances in Global Change Research ISBN: 9783030357979
Quantitative precipitation estimation (QPE) in mountainous regions remains a challenging task owing to its high spatiotemporal variability. Satellite-based radar observations at high resolution have the best potential to capture the spatial patterns
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffc2b5ca64087d46c804bd8280bf5707
https://doi.org/10.1007/978-3-030-35798-6_6
https://doi.org/10.1007/978-3-030-35798-6_6
Autor:
Pingping Xie, Shuyan Liu, Christopher Grassotti, Ralph Ferraro, Malarvizhi Arulraj, Shaorong Wu, Bob Kuligowski, Douglas Miller, Veljko Petkovic
Publikováno v:
Remote Sensing, Vol 13, Iss 2500, p 2500 (2021)
Two heavy rainfall events occurring in early 2020 brought flooding, flash flooding, strong winds, and tornadoes to the southern Appalachian Mountains. Part I of the study examined large-scale atmospheric contributions to the atmospheric river-influen
Autor:
Malarvizhi Arulraj, Ana P. Barros
Publikováno v:
Remote Sensing of Environment. 257:112355
Ground-clutter is a significant cause of missed-detection and underestimation of precipitation in complex terrain from space-based radars such as the Global Precipitation Measurement Mission (GPM) Dual-frequency Precipitation Radar (DPR). This resear
Autor:
Ana P. Barros, Malarvizhi Arulraj
Publikováno v:
Journal of Atmospheric and Oceanic Technology. 34:1963-1983
Detection of shallow warm rainfall remains a critical source of uncertainty in remote sensing of precipitation, especially in regions of complex topographic and radiometric transitions, such as mountains and coastlines. To address this problem, a new
Autor:
Malarvizhi Arulraj, Ana P. Barros
Publikováno v:
Remote Sensing of Environment. 231:111213
A physically-based framework to address the underestimation and missed detection errors in Quantitative Precipitation Estimates (QPE) from Global Precipitation Measurement (GPM) Precipitation Radar (PR) in regions of complex terrain is presented. The
Publikováno v:
Procedia Engineering. 38:2987-2997
The Markowitz mean-variance optimization algorithm, in conjunction with the enhanced Black Litterman model for estimating expected return of asset returns of Bombay Stock Exchange (BSE), is developed to solve the asset allocation problem. The estimat