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Massimo Frezzotti

Bio: Massimo Frezzotti is an academic researcher from ENEA. The author has contributed to research in topics: Ice core & Ice sheet. The author has an hindex of 42, co-authored 104 publications receiving 5386 citations. Previous affiliations of Massimo Frezzotti include Nuclear Energy Agency & Environment Agency.


Papers
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Journal ArticleDOI
TL;DR: In this article, an overview of the various measurement techniques, related difficulties, and limitations of data interpretation; describe spatial characteristics of East Antarctic SMB and issues related to the spatial and temporal representativity of measurements; and provide recommendations on how to perform in situ measurements.
Abstract: The East Antarctic Ice Sheet is the largest, highest, coldest, driest, and windiest ice sheet on Earth. Understanding of the surface mass balance (SMB) of Antarctica is necessary to determine the present state of the ice sheet, to make predictions of its potential contribution to sea level rise, and to determine its past history for paleoclimatic reconstructions. However, SMB values are poorly known because of logistic constraints in extreme polar environments, and they represent one of the biggest challenges of Antarctic science. Snow accumulation is the most important parameter for the SMB of ice sheets. SMB varies on a number of scales, from small-scale features (sastrugi) to ice-sheet-scale SMB patterns determined mainly by temperature, elevation, distance from the coast, and wind-driven processes. In situ measurements of SMB are performed at single points by stakes, ultrasonic sounders, snow pits, and firn and ice cores and laterally by continuous measurements using ground-penetrating radar. SMB for large regions can only be achieved practically by using remote sensing and/or numerical climate modeling. However, these techniques rely on ground truthing to improve the resolution and accuracy. The separation of spatial and temporal variations of SMB in transient regimes is necessary for accurate interpretation of ice core records. In this review we provide an overview of the various measurement techniques, related difficulties, and limitations of data interpretation; describe spatial characteristics of East Antarctic SMB and issues related to the spatial and temporal representativity of measurements; and provide recommendations on how to perform in situ measurements.

489 citations

Journal ArticleDOI
TL;DR: In this article, a database of surface Antarctic snow isotopic composition is constructed using available measurements, with an estimate of data quality and local variability, and the capacity of theoretical isotopic, regional, and general circulation atmospheric models to reproduce the observed features and assess the role of moisture advection in spatial deuterium excess fluctuations.
Abstract: A database of surface Antarctic snow isotopic composition is constructed using available measurements, with an estimate of data quality and local variability. Although more than 1000 locations are documented, the spatial coverage remains uneven with a majority of sites located in specific areas of East Antarctica. The database is used to analyze the spatial variations in snow isotopic composition with respect to geographical characteristics (elevation, distance to the coast) and climatic features (temperature, accumulation) and with a focus on deuterium excess. The capacity of theoretical isotopic, regional, and general circulation atmospheric models (including “isotopic” models) to reproduce the observed features and assess the role of moisture advection in spatial deuterium excess fluctuations is analyzed.

351 citations

Journal ArticleDOI
Julien Emile-Geay1, Nicholas P. McKay2, Darrell S. Kaufman2, Lucien von Gunten, Jianghao Wang3, Kevin J. Anchukaitis4, Nerilie J. Abram5, Jason A. Addison6, Mark A. J. Curran7, Mark A. J. Curran8, Michael N. Evans9, Benjamin J. Henley10, Zhixin Hao, Belen Martrat11, Belen Martrat12, Helen McGregor13, Raphael Neukom14, Gregory T. Pederson6, Barbara Stenni15, Kaustubh Thirumalai16, Johannes P. Werner17, Chenxi Xu18, Dmitry Divine19, Bronwyn C. Dixon10, Joelle Gergis10, Ignacio A. Mundo20, Takeshi Nakatsuka, Steven J. Phipps8, Cody C. Routson2, Eric J. Steig21, Jessica E. Tierney4, Jonathan J. Tyler22, Kathryn Allen10, Nancy A. N. Bertler23, Jesper Björklund24, Brian M. Chase25, Min Te Chen26, Edward R. Cook27, Rixt de Jong14, Kristine L. DeLong28, Daniel A. Dixon29, Alexey A. Ekaykin30, Alexey A. Ekaykin31, Vasile Ersek32, Helena L. Filipsson33, Pierre Francus34, Mandy Freund10, Massimo Frezzotti, Narayan Prasad Gaire35, Narayan Prasad Gaire36, Konrad Gajewski37, Quansheng Ge, Hugues Goosse38, Anastasia Gornostaeva, Martin Grosjean14, Kazuho Horiuchi39, Anne Hormes40, Katrine Husum19, Elisabeth Isaksson19, Selvaraj Kandasamy41, Kenji Kawamura42, Kenji Kawamura43, K. Halimeda Kilbourne9, Nalan Koc19, Guillaume Leduc44, Hans W. Linderholm40, Andrew Lorrey45, Vladimir Mikhalenko46, P. Graham Mortyn47, Hideaki Motoyama43, Andrew D. Moy8, Andrew D. Moy7, Robert Mulvaney48, Philipp Munz49, David J. Nash50, David J. Nash51, Hans Oerter52, Thomas Opel52, Anais Orsi53, Dmitriy V. Ovchinnikov54, Trevor J. Porter55, Heidi A. Roop56, Casey Saenger21, Masaki Sano, David J. Sauchyn38, Krystyna M. Saunders14, Krystyna M. Saunders57, Marit-Solveig Seidenkrantz58, Mirko Severi59, Xuemei Shao, Marie-Alexandrine Sicre60, Michael Sigl61, Kate E. Sinclair, Scott St. George62, Jeannine-Marie St. Jacques63, Jeannine-Marie St. Jacques64, Meloth Thamban65, Udya Kuwar Thapa62, Elizabeth R. Thomas48, Chris S. M. Turney66, Ryu Uemura67, A. E. Viau37, Diana Vladimirova31, Diana Vladimirova30, Eugene R. Wahl68, James W. C. White69, Zicheng Yu70, Jens Zinke71, Jens Zinke72 
University of Southern California1, Northern Arizona University2, MathWorks3, University of Arizona4, Australian National University5, United States Geological Survey6, Australian Antarctic Division7, University of Tasmania8, University of Maryland, College Park9, University of Melbourne10, University of Cambridge11, Spanish National Research Council12, University of Wollongong13, University of Bern14, Ca' Foscari University of Venice15, University of Texas at Austin16, University of Bergen17, Chinese Academy of Sciences18, Norwegian Polar Institute19, National University of Cuyo20, University of Washington21, University of Adelaide22, Victoria University of Wellington23, Swiss Federal Institute for Forest, Snow and Landscape Research24, University of Montpellier25, National Taiwan Ocean University26, Columbia University27, Louisiana State University28, University of Maine29, Saint Petersburg State University30, Arctic and Antarctic Research Institute31, Northumbria University32, Lund University33, Institut national de la recherche scientifique34, Tribhuvan University35, Nepal Academy of Science and Technology36, University of Ottawa37, Université catholique de Louvain38, Hirosaki University39, University of Gothenburg40, Xiamen University41, Japan Agency for Marine-Earth Science and Technology42, National Institute of Polar Research43, Aix-Marseille University44, National Institute of Water and Atmospheric Research45, Russian Academy of Sciences46, Autonomous University of Barcelona47, British Antarctic Survey48, University of Tübingen49, University of the Witwatersrand50, University of Brighton51, Alfred Wegener Institute for Polar and Marine Research52, Université Paris-Saclay53, Sukachev Institute of Forest54, University of Toronto55, University at Buffalo56, Australian Nuclear Science and Technology Organisation57, Aarhus University58, University of Florence59, Pierre-and-Marie-Curie University60, Paul Scherrer Institute61, University of Minnesota62, Concordia University63, University of Regina64, National Centre for Antarctic and Ocean Research65, University of New South Wales66, University of the Ryukyus67, National Oceanic and Atmospheric Administration68, University of Colorado Boulder69, Lehigh University70, Australian Institute of Marine Science71, Free University of Berlin72
TL;DR: A community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative, suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.
Abstract: Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.

260 citations

Journal ArticleDOI
11 Aug 2006-Science
TL;DR: There has been no statistically significant change in snowfall since the 1950s, indicating that Antarctic precipitation is not mitigating global sea level rise as expected, despite recent winter warming of the overlying atmosphere.
Abstract: Antarctic snowfall exhibits substantial variability over a range of time scales, with consequent impacts on global sea level and the mass balance of the ice sheets. To assess how snowfall has affected the thickness of the ice sheets in Antarctica and to provide an extended perspective, we derived a 50-year time series of snowfall accumulation over the continent by combining model simulations and observations primarily from ice cores. There has been no statistically significant change in snowfall since the 1950s, indicating that Antarctic precipitation is not mitigating global sea level rise as expected, despite recent winter warming of the overlying atmosphere.

229 citations

Journal ArticleDOI
TL;DR: In this article, a temperature record from the Talos Dome ice core, located in the Ross Sea sector of East Antarctica has been suggested to be synchronous with Northern Hemisphere climate change, pointing to differences in the climate evolution of the Indo-Pacific and Atlantic sectors of Antarctica.
Abstract: Ice-core records of climate from Greenland and Antarctica show asynchronous temperature variations on millennial timescales during the last glacial period 1 . The warming during the transition from glacial to interglacial conditions was markedly different between the hemispheres, a pattern attributed to the thermal bipolar see-saw 2 . However, a record from the Ross Sea sector of East Antarctica has been suggested to be synchronous with Northern Hemisphere climate change 3 . Here we present a temperature record from the Talos Dome ice core, also located in the Ross Sea sector. We compare our record with ice-core analyses from Greenland, based on methane synchronization 4 , and find clearly asynchronous temperature changes during the deglaciation. We also find distinct differences in Antarctic records, pointing to differences in the climate evolution of the Indo-Pacific and Atlantic sectors of Antarctica. In the Atlantic sector, we find that the rate of warming slowed between 16,000 and 14,500 years ago, parallel with the deceleration of the rise in atmospheric carbon dioxide concentrations and with a slight cooling over Greenland. In addition, our chronology supports the hypothesis that the cooling of the Antarctic Cold Reversal is synchronous with the Bolling‐Allerod warming in the northern hemisphere 14,700 years ago 5 . The period from about 8 to 25kyr before present (bp) includes the climate transition from the last glacial to the Holocene. As documented from polar ice cores and other climate archives, the pattern of climate changes throughout this transition is different between Antarctica and the surrounding Southern Ocean and the Northern Hemisphere. The steady Antarctic deglacial warming reaches a first maximum (Antarctic Isotopic Maximum AIM1; ref.1)followedbyaninterruptiontowardscoolerconditionsduring the Antarctic Cold Reversal (ACR). Conversely, Greenland records show two rapid-warming phases at the onset of the Dansgaard Oeschger-1(DO1)event(BllingAller dinterstadial,B/A)andthe

217 citations


Cited by
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Book Chapter
01 Jan 2013
TL;DR: The authors assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system.
Abstract: This chapter assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system. Changes are expressed with respect to a baseline period of 1986-2005, unless otherwise stated.

2,253 citations

Journal ArticleDOI
TL;DR: Bedmap2 as discussed by the authors is a suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1.
Abstract: We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved data-coverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72 m lower and the area of ice sheet grounded on bed below sea level is increased by 10%. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets.

1,678 citations

Journal ArticleDOI
TL;DR: This paper attempts to survey and summarize the recent research and development of EMD in fault diagnosis of rotating machinery, providing comprehensive references for researchers concerning with this topic and helping them identify further research topics.

1,410 citations

Journal ArticleDOI
30 Nov 2012-Science
TL;DR: There is good agreement between different satellite methods—especially in Greenland and West Antarctica—and that combining satellite data sets leads to greater certainty, and the mass balance of Earth’s polar ice sheets is estimated by combining the results of existing independent techniques.
Abstract: We combined an ensemble of satellite altimetry, interferometry, and gravimetry data sets using common geographical regions, time intervals, and models of surface mass balance and glacial isostatic adjustment to estimate the mass balance of Earth’s polar ice sheets. We find that there is good agreement between different satellite methods—especially in Greenland and West Antarctica—and that combining satellite data sets leads to greater certainty. Between 1992 and 2011, the ice sheets of Greenland, East Antarctica, West Antarctica, and the Antarctic Peninsula changed in mass by –142 ± 49, +14 ± 43, –65 ± 26, and –20 ± 14 gigatonnes year−1, respectively. Since 1992, the polar ice sheets have contributed, on average, 0.59 ± 0.20 millimeter year−1 to the rate of global sea-level rise.

1,215 citations