E
Eugenia Kalnay
Researcher at University of Maryland, College Park
Publications - 269
Citations - 56732
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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The 1998 Oklahoma–Texas Drought: Mechanistic Experiments with NCEP Global and Regional Models
Song-You Hong,Eugenia Kalnay +1 more
TL;DR: In this article, the origin and maintenance of the 1998 Oklahoma-Texas (OK-TX) drought were investigated using the National Centers for Environmental Prediction (NCEP) global and regional models.
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MOS, Perfect Prog, and Reanalysis
TL;DR: In this paper, an alternative method (called RAN) is examined that combines model output statistics and perfect prog, while at the same time utilizing the information in reanalysis data.
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Impact Of Satellite Temperature Sounding And Wind Data On Numerical Weather Prediction
TL;DR: In this article, a review of simulation studies and real-data experiments that were conducted to assess the impact of satellite observations on numerical weather prediction is presented, showing that while there has been some redundancy between observing systems, satellite data have made significant contributions toward improving global forecasting.
A further assessment of vegetation feedback on decadal Sahel rainfall variability
TL;DR: In this article, the effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM (SPEEDY) is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes.
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ENSO Bred Vectors in Coupled Ocean–Atmosphere General Circulation Models
TL;DR: In this paper, a breeding method has been implemented in the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Coupled General Circulation Model (CGCM) with the goal of improving operational seasonal to interannual climate predictions through ensemble forecasting and data assimilation.