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Eugenia Kalnay

Bio: Eugenia Kalnay is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Data assimilation & Ensemble Kalman filter. The author has an hindex of 61, co-authored 259 publications receiving 52574 citations. Previous affiliations of Eugenia Kalnay include Goddard Space Flight Center & Eötvös Loránd University.


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TL;DR: A new, local formulation of the ensemble Kalman Filter approach for atmospheric data assimilation based on the hypothesis that, when the Earth's surface is divided up into local regions of moderate size, vectors of the forecast uncertainties in such regions tend to lie in a subspace of much lower dimension than that of the full atmospheric state vector of such a region.
Abstract: In this paper, we introduce a new, local formulation of the ensemble Kalman Filter approach for atmospheric data assimilation. Our scheme is based on the hypothesis that, when the Earth's surface is divided up into local regions of moderate size, vectors of the forecast uncertainties in such regions tend to lie in a subspace of much lower dimension than that of the full atmospheric state vector of such a region. Ensemble Kalman Filters, in general, assume that the analysis resulting from the data assimilation lies in the same subspace as the expected forecast error. Under our hypothesis the dimension of this subspace is low. This implies that operations only on relatively low dimensional matrices are required. Thus, the data analysis is done locally in a manner allowing massively parallel computation to be exploited. The local analyses are then used to construct global states for advancement to the next forecast time. The method, its potential advantages, properties, and implementation requirements are illustrated by numerical experiments on the Lorenz-96 model. It is found that accurate analysis can be achieved at a cost which is very modest compared to that of a full global ensemble Kalman Filter.

563 citations

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TL;DR: New evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate is presented and it is shown that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually.
Abstract: The biophysical effects of forests on climate have been extensively studied with climate models. However, models cannot accurately reproduce local climate effects due to their coarse spatial resolution and uncertainties, and field observations are valuable but often insufficient due to their limited coverage. Here we present new evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate. Results show that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually; and boreal forests have strong warming in winter and moderate cooling in summer with net warming annually. The spatiotemporal cooling or warming effects are mainly driven by the two competing biophysical effects, evapotranspiration and albedo, which in turn are strongly influenced by rainfall and snow. Implications of our satellite-based study could be useful for informing local forestry policies.

435 citations

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TL;DR: Before 7 December 1992, NMC was producing a single global forecast through 10 days with the highest-resolution (T126) version possible of its medium-range forecast model, but now, based an experiments that showed no adverse impac...
Abstract: On 7 December 1992 NMC began operational ensemble prediction. The ensemble configuration provides 14 independent forecasts every day, verifying on days 1 through 10. The ensemble members are generated through a combination of time lagging [Lagged-Average Forecasting] and a new method, Breeding of Growing Modes (Toth and Kalnay). In adopting the ensemble approach, NMC explicitly recognizes that forecasts are stochastic, not deterministic, in nature. There is no single solution, only an array of possibilities, and forecast ensembles provide a rational basis for assessing the range and likelihood of alternative scenarios. Given the near saturation of computer resources at NMC, implementation of ensemble prediction required a trade-off between model resolution and multiple runs. Before 7 December 1992, NMC was producing a single global forecast through 10 days with the highest-resolution (T126) version possible of its medium-range forecast model. Now, based an experiments that showed no adverse impac...

340 citations

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TL;DR: Dynamical Seasonal Prediction (DSP) is an informally coordinated multi-institution research project to investigate the predictability of seasonal mean atmospheric circulation and rainfall as mentioned in this paper.
Abstract: Dynamical Seasonal Prediction (DSP) is an informally coordinated multi-institution research project to investigate the predictability of seasonal mean atmospheric circulation and rainfall. The basic idea is to test the feasibility of extending the technology of routine numerical weather prediction beyond the inherent limit of deterministic predictability of weather to produce numerical climate predictions using state-of-the-art global atmospheric models. Atmospheric general circulation models (AGCMs) either forced by predicted sea surface temperature (SST) or as part of a coupled forecast system have shown in the past that certain regions of the extratropics, in particular, the Pacific-North America (PNA) region during Northern Hemisphere winter, can be predicted with significant skill especially during years of large tropical SST anomalies. However, there is still a great deal of uncertainty about how much the details of various AGCMs impact conclusions about extratropical seasonal prediction an...

319 citations

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TL;DR: In this article, the authors describe the global numerical weather prediction system of the National Meteorological Center and review recent improvements, the evolution in skill, and current research projects and plans.
Abstract: In this paper we describe the global numerical weather prediction system of the National Meteorological Center, and review recent improvements, the evolution in skill, and current research projects and plans.

303 citations


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TL;DR: The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible, except that the horizontal resolution is T62 (about 210 km) as discussed by the authors.
Abstract: The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided b...

28,145 citations

Journal ArticleDOI
TL;DR: ERA-Interim as discussed by the authors is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which will extend back to the early part of the twentieth century.
Abstract: ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright © 2011 Royal Meteorological Society

22,055 citations

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22 Jul 2005-Science
TL;DR: Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity.
Abstract: Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet’s resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

10,117 citations

01 Jan 2007
TL;DR: Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris.
Abstract: Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe

7,720 citations