Toward New Applications of the Adjoint Sensitivity Tools in Data Assimilation
D.N. Daescu and R.H. Langland
In Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III).
Seon K. Park and Liang Xu (Editors). Print ISBN: 978-3-319-43414-8, Online ISBN: 978-3-319-43415-5, Springer 2017.

The Adjoint Sensitivity Guidance to Diagnosis and Tuning of Error Covariance Parameters
D.N. Daescu and R.H. Langland
In Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II), p. 205--232.
Seon K. Park and Liang Xu (Editors), ISBN: 978-3-642-35087-0, Springer 2013.

Sensitivity Analysis in Nonlinear Variational Data Assimilation: Theoretical Aspects and Applications
D.N. Daescu and I.M. Navon
In Advanced Numerical Methods for Complex Environmental Models: Needs and Availability, p. 276--300.
Istvan Farago, Agnes Havasi, and Zahari Zlatev (Editors). Bentham Science Publishers, ISBN: 978-1-60805-777-1, eISBN: 978-1-60805-778-8, 2013.

Sensitivity Analysis Methods in Air Quality Models
D.N. Daescu
In Modelling of Pollutants in Complex Environmental Systems: Volume I, p. 241-259.
Grady Hanrahan (Editor), ILM Publications 2009.

An FSO-based Optimization Framework for Improved Observation Performance: Theoretical Formulation and Experiments with NAVDAS-AR/NAVGEM
D.N. Daescu, R.H. Langland
Monthly Weather Review, 150 (6), 1335-1353, 2022.

The Quest for Model Uncertainty Quantification: A Hybrid Ensemble and Variational Data Assimilation Framework
P. Abbaszadeh, H. Moradkhani, D.N. Daescu
Water Resources Research, vol. 55 (3), 2407--2431, 2019.

Sensitivity of the model error parameter specification in weak-constraint four-dimensional variational data assimilation
J.A. Shaw, D.N. Daescu
Journal of Computational Physics, 343, 115-129, 2017.

Accounting for satellite radiance inter-channel correlations in GSI
R. Todling, W. Gu, D.N. Daescu
JCSDA Quarterly , No. 52, 6--9, 2015.

Error covariance sensitivity and impact estimation with adjoint 4D-Var: theoretical aspects and first applications to NAVDAS-AR
D.N. Daescu, R.H. Langland
Quarterly Journal of the Royal Meteorological Society, 139: 226-241, 2013.

Effect of random perturbations on adaptive observation techniques
M.J. Hossen, I. M. Navon, D.N. Daescu
International Journal for Numerical Methods in Fluids, 69: 110-123, 2012.

Ensemble methods for dynamic data assimilation of chemical observations in atmospheric models
A. Sandu, E. Constantinescu, G.R. Carmichael, T. Chai, D. Daescu, J.H. Seinfeld
Journal of Algorithms and Computational Technology , Volume 5, No. 4, 667-692, 2011.

Observation targeting with a second-order adjoint method for increased predictability
H.C. Godinez and D.N. Daescu
Computational Geosciences , 15, 477-488, 2011.

Adjoint sensitivity of the model forecast to data assimilation system error covariance parameters
D.N. Daescu and R. Todling
Quarterly Journal of the Royal Meteorological Society, 136, 2000-2012, 2010.

On the deterministic observation impact guidance: a geometrical perspective
D.N. Daescu
Monthly Weather Review, 137, 3567-3574, 2009.

Adjoint estimation of the variation in model functional output due to the assimilation of data
D.N. Daescu and R. Todling
Monthly Weather Review, 137 (5), 1705-1716, 2009.

A single particle impact model for motion in avalanches
J.J.P. Veerman, D. Daescu, M.J. Romero-Valles, and P.J. Torres
Physica D: Nonlinear Phenomena, 238 (18), 1897--1908, 2009.

On the sensitivity equations of four-dimensional variational (4D-Var) data assimilation
D.N. Daescu
Monthly Weather Review, 136 (8), 3050-3065, 2008.

A Dual-Weighted Approach to Order Reduction in 4D-Var Data Assimilation
D.N. Daescu and I.M. Navon
Monthly Weather Review, 136, 1026-1041, 2008.

Predicting Air Quality: Improvements through advanced methods to integrate models and measurements
GR Carmichael, A Sandu, T Chai, DN Daescu, EM Constantinescu, Y Tang
Journal of Computational Physics, 227, 3540-3571, 2008.

Efficiency of a POD-based reduced second order adjoint model in 4D-Var data assimilation
D.N. Daescu and I.M. Navon
International Journal for Numerical Methods in Fluids, 53:985-1004, 2007.

Initiation of ensemble data assimilation
Zupanski M, Fletcher SJ, Navon IM, Uzunoglu B, Heikes RP, Randall DA, Ringler TD, Daescu DN
Tellus Series A - Dynamic Meteorology and Oceanography, 58 (2): 159-170 MAR 2006

Chemical data assimilation of Transport and Chemical Evolution over the Pacific (TRACE-P) aircraft measurements
T.F. Chai, G.R. Carmichael, A. Sandu, Y.H. Tang, D.N. Daescu
Journal of Geophysical Research-Atmospheres 111 (D2): Art. No. D02301 JAN 17 2006

Adjoint sensitivity analysis of regional air quality models
A. Sandu, D.N. Daescu, G.R. Carmichael, and Tianfeng Chai
Journal of Computational Physics, 204, 222-252, 2005

Adaptive observations in the context of 4D-Var data assimilation
D.N. Daescu and I.M. Navon
Meteorology and Atmospheric Physics, vol. 85, 205-226, 2004

Direct and adjoint sensitivity analysis of chemical kinetic systems with KPP: I - theory and software tools
A. Sandu, D.N. Daescu, and G.R. Carmichael
Atmospheric Environment 37 (36), 5083-5096, 2003

Direct and adjoint sensitivity analysis of chemical kinetic systems with KPP: II - numerical validation and applications
D.N. Daescu, A. Sandu, and G.R. Carmichael
Atmospheric Environment 37 (36), 5097-5114, 2003

An analysis of a hybrid optimization method for variational data assimilation
D.N. Daescu and I.M. Navon
International Journal of Computational Fluid Dynamics, Vol. 17, No. 4, 299-306, 2003

An adjoint sensitivity method for the adaptive location of the observations in air quality modeling
D.N. Daescu and G.R. Carmichael
Journal of the Atmospheric Sciences, Vol. 60, No. 2, 434-450, 2003

A communication library for the parallelization of air quality models on structured grids
Philipp Miehe, Adrian Sandu, Gregory R. Carmichael, Dacian N. Daescu
Atmospheric Environment, 36 (24) 3917-3930, 2002.

Second order information in data assimilation
F.-X. Le Dimet, I.M. Navon, and D.N. Daescu
Monthly Weather Review, Vol. 130, No. 3 , 629-648, 2002

Adjoint Implementation of Rosenbrock Methods Applied to Variational Data Assimilation Problems
D.N. Daescu, G.R. Carmichael, and A. Sandu
Journal of Computational Physics 165 (2), 496-510, 2000

Computational challenges of modelling interactions between aerosol and gas phase processes in large‐scale air pollution models
Gregory R. Carmichael, Adrian Sandu, Chul H. Song, Shan He, Mahesh J. Phadnis, Dacian Daescu, Valeriu Damian‐Iordache, Florian A. Potra
Environmental Management and Health Vol. 10 Issue: 4, pp.224-235, 1999

Innovation-weight parametrization in data assimilation: formulation & analysis with NAVDAS-AR/NAVGEM
Daescu DN, Langland RH
IFAC-PapersOnLine, Vol 49, Issue 18, 176--181, 2016.
Proceedings to the 10th IFAC Symposium on Nonlinear Control Systems , Monterey, CA, August 23-25, 2016.

An Ensemble Approach to Weak-Constraint Four-Dimensional Variational Data Assimilation
Shaw JA, Daescu DN
Procedia Computer Science, Volume 80, 496--506.
Proceedings to the 2016 International Conference on Computational Science.

Forecast sensitivity to the observation error covariance in variational data assimilation
D.N. Daescu
Procedia Computer Science, Volume 1, Issue 1, May 2010, 1271-1279.
Proceedings to the 10th International Conference on Computational Science
Amsterdam, The Netherlands, May 31 - June 2, 2010.

Sensitivity analysis in variational data assimilation and applications
D.N. Daescu
ECMWF Workshop on diagnostics of data assimilation system performance, 15-17 June 2009, 107-116.
ECMWF, Reading, U.K.

A second order adjoint method to targeted observations
Godinez H, Daescu DN
Lecture Notes in Computer Science, Volume 5545, 322-331, ScienceSpringer Berlin/Heidelberg.
Proceedings to the 9th International Conference on Computational Science, Baton Rouge, LA, USA, May 25-27, 2009.

Predicting Air Quality: Current Status and Future Directions
Carmichael GR, Sandu A, Chai T, Daescu DN, Constantinescu EM, Tang Y
Air Pollution Modeling and Its Application XIX
NATO Science for Peace and Security Series C: Environmental Security, 481-495, Springer 2008.

The impact of background error on incomplete observations for 4D-Var data assimilation with the FSU GSM
Navon IM, Daescu DN, Liu Z. Lecture Notes in Computer Science, vol 3515/2005, 837-844.
5th International Conference on Computational Science, Atlanta, GA, May 22-25, 2005 Proceedings, Part II.

Computational aspects of chemical data assimilation into atmospheric models
Carmichael GR, Daescu DN, Sandu A, Chai TF
Lecture Notes in Computer Science 2660: 269-278, 2003. Proceedings Computational Science - ICCS 2003, PT IV.

Adjoint sensitivity analysis applied to the adaptive location of the observations
D.N. Daescu and G.R. Carmichael
Air Pollution Modeling and Simulation, Proceedings 2nd Conference on Air Pollution Modeling and Simulation, April 9-12, 2001 Paris, France.
Bruno Sportisse (Ed.), p. 476-488, Springer 2002.

Adjoint data assimilation for aerosol dynamic equations
A. Sandu, D.N. Daescu and G.R. Carmichael
Air Pollution Modeling and Simulation, Proceedings 2nd Conference on Air Pollution Modeling and Simulation, April 9-12, 2001 Paris, France.
Bruno Sportisse (Ed.), p. 319-331, Springer 2002.

Coupled Transport-Chemistry Computations in 4D-Var Data Assimilation for Air Pollution Models
D. Daescu and G.R. Carmichael
IMA Workshop, Atmospheric Modeling, March 15-19, 2000 Minneapolis. IMA Volume 130, Atmospheric Modeling, p. 153-164, Springer-Verlag 2002.

Adjoint Implementation of Rosenbrock Methods Applied to Variational Data Assimilation
D. Daescu, G.R. Carmichael and A. Sandu
Millennium NATO/CCMS International Technical Meeting on Air Pollution and Its Applications, May 15-19, 2000 Colorado, p. 346-354.

Computational challenges of modeling interactions between aerosol and gas phase processes in large scale air pollution models
G.R. Carmichael and Coauthors
Large-Scale Computations in Air Pollution Modeling, p. 99-136, Kluwer Publishers, 1999.