S
Sajad Vahedizade
Researcher at University of Minnesota
Publications - 4
Citations - 25
Sajad Vahedizade is an academic researcher from University of Minnesota. The author has contributed to research in topics: Snow & Radiometer. The author has an hindex of 2, co-authored 2 publications receiving 5 citations.
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Journal ArticleDOI
Applications of a cloudsat-trmm and cloudsat-gpm satellite coincidence dataset
F. Joseph Turk,Sarah Ringerud,Sarah Ringerud,Andrea Camplani,Daniele Casella,Randy J. Chase,Ardeshir Ebtehaj,Jie Gong,Jie Gong,Mark S. Kulie,Guosheng Liu,Lisa Milani,Lisa Milani,Giulia Panegrossi,Ramon Padullés,Jean François Rysman,Paolo Sanò,Sajad Vahedizade,Norman B. Wood +18 more
TL;DR: In this article, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) is demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors.
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Passive Microwave Signatures and Retrieval of High-Latitude Snowfall Over Open Oceans and Sea Ice: Insights From Coincidences of GPM and CloudSat Satellites
TL;DR: In this article, the authors studied changes in microwave signals of oceanic snowfall in response to the formation of snow-covered sea ice using active and passive coincident data from the radar and radiometer onboard the CloudSat and the global precipitation measurement satellites.
Journal ArticleDOI
Evaluation of Snowfall Retrieval Performance of GPM Constellation Radiometers Relative to Spaceborne Radars
Yalei You,George J. Huffman,Veljko Petkovic,Lisa Milani,John Xun Yang,Ardeshir Ebtehaj,Sajad Vahedizade,Guojun Gu +7 more
TL;DR: In this paper , the authors assessed the level-2 snowfall retrieval results from 11 passive microwave radiometers generated by the Version 5 Goddard profiling algorithm (GPROF) relative to two space-borne radars: CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Measurement (GPM) Ku-band Precisitation Radar (KuPR), and conclude that all 11 sensors severely underestimate the snowfall intensity, which propagates to the widely used level 3 precipitation product (i.e., Integrated Multi-satellite Retrievals for GPM [IMERG]).
Journal ArticleDOI
On the effects of cloud water content on passive microwave snowfall retrievals
Sajad Vahedizade,Ardeshir Ebtehaj,Sagar K. Tamang,Yalei You,Giulia Panegrossi,Sarah Ringerud,F. Joseph Turk +6 more
TL;DR: In this article , the Neyman-Pearson (NP) hypothesis testing is used to separate the imposter and genuine brightness temperatures based on their associated values of cloud ice (IWP) and liquid water path (LWP), given by coincidences of CloudSat Profiling Radar (CPR) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI).