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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.


Papers
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Journal ArticleDOI
05 Sep 2013-Tellus A
TL;DR: In this article, the impact of the assimilated observations on the 24-hour forecasts is estimated with the ensemble-based method proposed by Kalnay et al. using an ensemble Kalman filter (EnKF).
Abstract: The impacts of the assimilated observations on the 24-hour forecasts are estimated with the ensemble-based method proposed by Kalnay et al. using an ensemble Kalman filter (EnKF). This method estimates the relative impact of observations in data assimilation similar to the adjoint-based method proposed by Langland and Baker but without using the adjoint model. It is implemented on the National Centers for Environmental Prediction Global Forecasting System EnKF that has been used as part of operational global data assimilation system at NCEP since May 2012. The result quantifies the overall positive impacts of the assimilated observations and the relative importance of the satellite radiance observations compared to other types of observations, especially for the moisture fields. A simple moving localisation based on the average wind, although not optimal, seems to work well. The method is also used to identify the cause of local forecast failure cases in the 24-hour forecasts. Data-denial experiments of the observations identified as producing a negative impact are performed, and forecast errors are reduced as estimated, thus validating the impact estimation. Keywords: data assimilation, observation impact, ensemble Kalman filter, skill dropout, ensemble sensitivity (Published: 5 September 2013) Citation: Tellus A 2013, 65 , 20038, http://dx.doi.org/10.3402/tellusa.v65i0.20038

52 citations

Journal ArticleDOI
TL;DR: In this paper, a method to assimilate observed rain rates in the Tropics for improving initial fields in forecast models is proposed, which consists of a 6-h integration of a numerical forecast model; the specific humidity at every time step at each grid point is modified (nudged) in such a way that the total model precipitation accumulated during this integration becomes very close to that observed.
Abstract: A method to assimilate observed rain rates in the Tropics for improving initial fields in forecast models is proposed. It consists of a 6-h integration of a numerical forecast model; the specific humidity at every time step at each grid point is modified (nudged) in such a way that the total model precipitation accumulated during this integration becomes very close to that observed. An increase in the model precipitation is achieved by moistening the lower troposphere above a grid point with prescribed supersaturation; a decrease in the model rainfall is brought about by decreasing the specific humidity in the lower troposphere in proportion to the difference between the model and reference specific humidity profiles. The modified values depend on the difference between the model and target precipitation. The depth of the atmospheric column in which the humidity is changed is proportional to the target rain rate. Quality criteria of a rain assimilation procedure are proposed. The quality of the a...

52 citations

Journal ArticleDOI
TL;DR: In this paper, the authors focus on the impact of advanced variance inflation methods and vertical localization of column CO2 data on the analysis of CO2 and use the Local Ensemble Transform Kalman Filter (LETKF) within an Observing System Simulation Experiments framework.
Abstract: [1] We perform every 6 h a simultaneous data assimilation of surface CO2 fluxes and atmospheric CO2 concentrations along with meteorological variables using the Local Ensemble Transform Kalman Filter (LETKF) within an Observing System Simulation Experiments framework. In this paper, we focus on the impact of advanced variance inflation methods and vertical localization of column CO2 data on the analysis of CO2. With both additive inflation and adaptive multiplicative inflation, we are able to obtain encouraging multiseasonal analyses of surface CO2 fluxes in addition to atmospheric CO2 and meteorological analyses. Furthermore, we examine strategies for vertical localization in the assimilation of simulated CO2 from GOSAT that has nearly uniform sensitivity from the surface to the upper troposphere. Since atmospheric CO2is forced by surface fluxes, its short-term variability should be largest near the surface. We take advantage of this by updating observed changes only into the lower tropospheric CO2 rather than into the full column. This results in a more accurate analysis of CO2 in terms of both RMS error and spatial patterns. Assimilating synthetic CO2ground-based observations and CO2 retrievals from GOSAT and AIRS with the enhanced LETKF, we obtain an accurate estimation of the evolving surface fluxes even in the absence of any a priori information. We also test the system with a longer assimilation window and find that a short window with an efficient treatment for wind uncertainty is beneficial to flux inversion. Since this study assumes a perfect forecast model, future research will explore the impact of model errors.

52 citations

Journal ArticleDOI
TL;DR: In this article, a stepwise regression scheme was used to predict the forecast skill of the medium-range forecasts produced by the NMC global spectral model, and the most important predictor of skill was the agreement between the global forecast started at 0000 UTC, out to 6 days, and four other 12-h “older” forecasts (Japan Meteorological Agency, United Kingdom Meteorological Office and the European Centre for Medium-Range Weather Forecasts, as well as the average of the forecast with the previous day's forecast).
Abstract: In real time since 1990, the National Meteorological Center (NMC) has been running a system to predict the forecast skill of the medium-range forecasts produced by the NMC global spectral model. The predictors used are the agreement of an ensemble consisting of operational forecasts from various centers, the persistence in the forecast, and the amplitude of the anomalies. These predictors are used in a stepwise regression scheme, with the last 60 days used as training period, and the regional anomaly correlation of the 0000 UTC NMC global forecast is predicted from days 1 to 6. By far the most important predictor of skill is the agreement between the NMC global forecast started at 0000 UTC, out to 6 days, and four other 12-h “older” forecasts (Japan Meteorological Agency, United Kingdom Meteorological Office, and the European Centre for Medium-Range Weather Forecasts, as well as the average of the NMC forecast at 0000 UTC with the previous day's forecast). The other predictors have been selected ...

51 citations


Cited by
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Journal ArticleDOI
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

Journal ArticleDOI
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