M
Matthew A. Lazzara
Researcher at University of Wisconsin-Madison
Publications - 66
Citations - 2418
Matthew A. Lazzara is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Automatic weather station & Ice shelf. The author has an hindex of 23, co-authored 60 publications receiving 1988 citations. Previous affiliations of Matthew A. Lazzara include Cooperative Institute for Meteorological Satellite Studies & Madison Area Technical College.
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Journal ArticleDOI
Evaluating the highest temperature extremes in the antarctic
María de los Milagros Skansi,John C. King,Matthew A. Lazzara,Matthew A. Lazzara,Randall S. Cerveny,José Luis Stella,Susan Solomon,Philip Jones,David H. Bromwich,James A. Renwick,Christopher C. Burt,Thomas C. Peterson,Manola Brunet,Manola Brunet,Fatima Driouech,Russell S. Vose,Daniel S. Krahenbuhl +16 more
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Southern Ocean mesocyclones and polar lows from manually tracked satellite mosaics
Polina Verezemskaya,Polina Verezemskaya,Natalia Tilinina,Natalia Tilinina,Sergey Gulev,Sergey Gulev,Ian A. Renfrew,Matthew A. Lazzara +7 more
TL;DR: A new reference dataset of mesocyclone activity over the Southern Ocean has been developed from the manual analysis of high-resolution infrared satellite mosaics for winter 2004 as mentioned in this paper, which includes mesocyclones track, size, associated cloud vortex type and background synoptic conditions.
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The surface climatology of the Ross Ice Shelf Antarctica
TL;DR: Climate indices are compared to temperature and pressure data of four of the AWS with the longest observation periods, and significant correlation is found for most AWS in sea‐level pressure and temperature.
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Global satellite composites — 20 years of evolution
TL;DR: In infrared window composites were created by combining Geostationary Operational Environmental Satellite (GOES), and polar orbiting data from the SSEC Data Center and polar data acquired at McMurdo and Palmer stations, Antarctica.
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A Self-Organizing-Map-Based Evaluation of the Antarctic Mesoscale Prediction System Using Observations from a 30-m Instrumented Tower on the Ross Ice Shelf, Antarctica
TL;DR: In this paper, the authors used self-organizing maps (SOM) to identify characteristic potential temperature anomaly profiles observed at the 30m tower of a weather station on the Ross Ice Shelf, Antarctica.