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Dive into the research topics where David M. Legler is active.

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Featured researches published by David M. Legler.


Journal of Climate | 2009

A U.S. Clivar project to assess and compare the responses of global climate models to drought-related SST forcing patterns: Overview and results

Siegfried D. Schubert; David S. Gutzler; Hailan Wang; Aiguo Dai; T. Delworth; Clara Deser; Kirsten L. Findell; Rong Fu; Wayne Higgins; Martin P. Hoerling; Ben P. Kirtman; Randal D. Koster; Arun Kumar; David M. Legler; Dennis P. Lettenmaier; Bradfield Lyon; Víctor Magaña; Kingtse C. Mo; Sumant Nigam; Philip Pegion; Adam S. Phillips; Roger Pulwarty; David Rind; Alfredo Ruiz-Barradas; Jae Schemm; Richard Seager; Ronald E. Stewart; Max J. Suarez; Jozef Syktus; Mingfang Ting

Abstract The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern. One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific for...


Journal of Climate | 2001

Quantifying Uncertainties in NCEP Reanalyses Using High-Quality Research Vessel Observations

Shawn R. Smith; David M. Legler; Kathleen V. Verzone

Abstract The uncertainties in the NCEP–NCAR reanalysis (NCEPR) products are not well known. Using a newly developed, high-resolution, quality controlled, surface meteorology dataset from research vessels participating in the World Ocean Circulation Experiment (WOCE), regional and global uncertainties are quantified for the NCEPR air–sea fluxes and the component fields used to create those fluxes. For the period 1990–95, WOCE vessel and gridded NCEPR fields are matched in time and space. All in situ data are subject to data quality review to remove suspect data. Adjustment of ship observations to the reference height of the NCEPR variables, and calculation of air–sea fluxes from the in situ data are accomplished using bulk formulas that take atmospheric stability, height of the measurements, and other adjustments into consideration. The advantages of using this new set of WOCE ship observations include the ability to compare 6-h integrated fluxes (much of the ship data originate from automated observing sy...


Monthly Weather Review | 1987

Conjugate-Gradient Methods for Large-Scale Minimization in Meteorology

I. M. Navon; David M. Legler

Abstract During the last few years new meteorological variational analysis methods have evolved, requiring large-scale minimization of a nonlinear objective function described in terms of discrete variables. The conjugate-gradient method was found to represent a good compromise in convergence rates and computer memory requirements between simpler and more complex methods of nonlinear optimization. In this study different available conjugate-gradient algorithms are presented with the aim of assessing their use in large-scale typical minimization problems in meteorology. Computational efficiency and accuracy are our principal criteria. Four different conjugate-gradient methods, representative of up-to-date available scientific software, were compared by applying them to two different meteorological problems of interest using criteria of computational economy and accuracy. Conclusions are presented as to the adequacy of the different conjugate algorithms for large-scale minimization problems in different met...


Computers & Geosciences | 1991

VARIATM—A FORTRAN program for objective analysis of pseudostress wind fields using large-scale conjugate-gradient minimization

David M. Legler; I. M. Navon

Abstract A FORTRAN computer program is presented and documented which implements a new approach to objective analysis of pseudostress data over the Indian Ocean. (A pseudostress vector is defined as the wind components multiplied by the wind magnitude.) This method is a direct large-scale minimization approach of a cost functional expressed as a weighted sum of lack of fit to data as well as constraints on proximity to original observations and climatology, on a smoothing parameter and on kinematic equivalence to climatological patterns. Each of the constraints was weighted by selected coefficients controlling how closely the minimizing analysis fits each type of data or constraint. The functional operates on 7330 variables (i.e. two wind components at each grid location) and was minimized using a highly efficient memoryless quasi-Newton-like conjugate-gradient method. Use of an independent subjective analysis of the same data provide for a direct quantitative comparison and confirm the adequacy of the objective analysis. This scheme now has been adopted operationally to generate monthly average pseudostress wind values on a 1°-grid over the Indian Ocean.


Climatic Change | 1998

THE VALUE OF IMPROVED ENSO PREDICTION TO U.S. AGRICULTURE

Andrew R. Solow; Richard F. Adams; Kelly J. Bryant; David M. Legler; James J. O'Brien; Bruce A. McCarl; William Nayda; Rodney Weiher

The economic value of long-range weather prediction is measured by the increase in social welfare arising from the use of the prediction in economic decisionmaking. This paper describes a study of the economic value of ENSO prediction to U.S. agriculture. The interdisciplinary study involved the analysis of data and models from meteorology, plant science, and economics under a framework based on Bayesian decision analysis. The estimated annual value of perfect ENSO prediction to U.S. agriculture is


Monthly Weather Review | 1989

Objective Analysis of Pseudostress over the Indian Ocean Using a Direct-Minimization Approach

David M. Legler; I. M. Navon; James J. O'Brien

323 million.


Science | 1988

On the Prediction of the El Niño of 1986-1987

Tim P. Barnett; Nicholas E. Graham; Mark A. Cane; Stephen E. Zebiak; Sean C. Dolan; James J. O'Brien; David M. Legler

Abstract A variational approach is used to develop an objective analysis technique which produces monthly average 1-deg pseudostress vector fields over the Indian Ocean. A, cost functional is constructed which consists of five terms, each expressing a lack of fit to prescribed conditions. The first expresses the proximity to the input (first-guess) field. The second deals with the closeness of fit to the climatological value for that month. The third is a measure of data roughness, and the fourth and fifth are kinematic constraints on agreement of the curl and divergence of the results to the curl and divergence of the climatology. Each term also has a coefficient (weight) which determines how closely the minimization fits each lack of fit. These weights are determined by comparing the results using various weight combinations to an independent subjective analysis of the same dataset. The cost functional is minimized using the conjugate-gradient method. Results from various weight combinations are present...


Monthly Weather Review | 2000

Objectively Derived Daily “Winds” from Satellite Scatterometer Data

P. J. Pegion; Mark A. Bourassa; David M. Legler; James J. O’Brien

Three different classes of numerical models successfully predicted the occurrence of the El Ni�o of 1986-87 at lead times of 3 to 9 months. Although the magnitude and timing of predicted ocean surface temperatures were not perfect, these results suggest that routine prediction of moderate to lare El Ni�o events is feasible. The key to the success of the models lies in recognizing or simulating the low-frequency, large-scale changes in the tropical ocean-atmosphere system that give rise to El Ni�o events.


Eos, Transactions American Geophysical Union | 1997

Wind observations from new satellite and research vessels agree

Mark A. Bourassa; Michael H. Freilich; David M. Legler; W. Timothy Liu; James J. O'Brien

Abstract An objective technique is used to create regularly gridded daily “wind” fields from NASA scatterometer (NSCAT) observations for the Pacific Ocean north of 40°S. The objective technique is a combination of direct minimization, and cross validation with multigridding. The fields are created from the minimization of a cost function. The cost function is developed to maximize information from the observational data and minimize smoothing. Three constraints are in the cost function: a misfit to observations, a smoothing term, and a misfit of the curl. The second and third terms are relative to a background field. The influence of the background field is controlled by weights on the smoothing constraints. Weights are objectively derived by the method of cross validation. Cross validation is a process that removes observations from the input to the cost function and determines tuning parameters (weights) by the insensitivity of the removed observations to the output field. This method is computationally...


Climatic Change | 1999

Impact of ENSO-Related Climate Anomalies on Crop Yields in the U.S.

David M. Legler; Kelly J. Bryant; James J. O'Brien

An instrument designed to observe wind speeds and directions over the ocean surface has realized the promise suggested by the first spaceborne scatterometer on the SeaSAT satellite nearly 20 years ago. In 1996, NSCAT (NASA Scatterometer) rode into orbit on the Japanese satellite ADEOS and gathered 8.5 months of valuable wind data. NSCATs unprecedented ability to determine wind speed and direction over 90% of the icefree global water surface with a 25 km resolution in 2 days should have profound impacts on oceanographic and meteorological applications. Prior to these applications, however, the uncertainty of NSCAT data must be determined from calibration and validation with in-situ observations. Comparison of NSCAT wind speeds and direction to those observed from research vessels shows an extremely good match. The analysis suggests that NSCAT winds appear to be sufficiently accurate for use in forcing ocean models.

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Shawn R. Smith

Florida State University

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Norman J. Rosenberg

Pacific Northwest National Laboratory

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Andrew R. Solow

Woods Hole Oceanographic Institution

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I. M. Navon

Florida State University

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Robert A. Brown

Pacific Northwest National Laboratory

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