OSSE related references

The list includes selected conference papers.


Andersson, Erik and Michiko Masutani 2010:  Collaboration on Observing System Simulation Experiments (Joint OSSE), ECMWF News Letter No. 123, Spring 2010, 14-16. http://www.ecmwf.int/publications/newsletters/pdf/123.pdf

Arnold, C. P., Jr.  and C. H. Dey, 1986: Observing-systems simulation experiments: Past, present, and future. Bull. Amer., Meteor. Soc., 67, 687-695.

Atlas, R., E. Kalnay, J. Susskind, D. Reuter, W. E. Baker and M. Halem, (1984) Simulation studies of the impact of advanced observing systems on numerical weather prediction. Preprints, Conf. on Satellite/Remote Sensing and Appl., Clearwater Beach, FL. Amer. Meteor. Soc., Boston, MA, 283-287.  [Available online at http://docs.lib.noaa.gov/rescue/TIROS/TL798M4C621984.pdf ]

Atlas, R., E. Kalnay, J. Susskind, W.E. Baker and M. Halem, 1985. Simulation studies of the impact of future observing systems on weather prediction. Proc. Seventh Conf. on NWP, 145-151.

Atlas, R., et al.,2015: Observing System Simulation Experiments (OSSEs) to Evaluate the Potential Impact of an Optical Autocovariance Wind Lidar (OAWL) on Numerical Weather Prediction, J. Atmos. Oceanic Technol, DOI: 10.1175/JTECH-D-15-0038.1_ 2015

Atlas, R. 1997: Atmospheric observations and experiments to assess their usefulness in
data assimilation.  Journal of the Meteorological Society of Japan, 75, 111-130.

Baker, Wayman E. , Robert Atlas, Carla Cardinali, Amy Clement, George D. Emmitt, Bruce M. Gentry, R. Michael Hardesty, Erland Källén, Michael J. Kavaya, Rolf Langland, Zaizhong Ma, Michiko Masutani, Will McCarty, R. Bradley Pierce, Zhaoxia Pu, Lars Peter Riishojgaard, James Ryan, Sara Tucker, Martin Weissmann, and James G. Yoe 2013:Lidar-Measured Wind Profiles – The Missing Link in the Global Observing System.  Bull. Amer. Meteor. Soc.,  Vol. 95, 543-564. DOI: 10.1175/BAMS-D-12-00164.1.

Beesley, J., C. Bretherton, C. Jakob, E. Andreas, J. Intrieri, and T.
Uttal (2000), A comparison of cloud and boundary layer variables in the
ECMWF forecast model with observations at Surface Heat Budget of the
Arctic Ocean (SHEBA) ice camp, J. Geophys. Res., 105(D10), 12337-12349.


Becker, B. D., H. Roquet, and A. Stoffelen 1996: A simulated future atmospheric observation database including ATOVS, ASCAT, and DWL. BAMS, 77, 2279-2294.


Boukabara, S.-A., I .Moradi, R. Atlas,S. P. F. Casey, L. Cucurull, R. N. Hoffman, K. Ide, V. K. Kumar, R. Li, Z. Li,M. Masutani, N. Shahroudi, J. S. Woollen, Y. Zhou, 2016: Community global observing system simulation experiment (OSSE) package :: CGOP. description and usage. J. Atmospheric Oceanic Technology, 33(XX):XXXX–XXXX, XXX 2016. Submitted. doi:JTECH-D-16-0012.1.  (Early online Release)

Casey, S.-P., L. P. Riishojgaard, M. Masutani, J. S. Woollen, T. Zhu, and R. Atlas 2013: Observing System Simulation Experiments for an EarlyMorningOrbit Meteorological Satellite, JCSDA Quarterly, No 42, March 2013. http://www.jcsda.noaa.gov/documents/newsletters/201303JCSDAQuarterly.pdf

Casey, S.-P., L. P. Riishojgaard, M. Masutani, J. S. Woollen, T. Zhu, and R. Atlas 2013: Observing System Simulation Experiments for an Early-Morning-Orbit Meteorological Satellite in the Joint Center for Satellite Data Assimilation.  Joint EUMETSAT/AMS Meteorological Satellite Conference, Vienna September 2013.

Committee on Earth Science and Applications from Space:  2007: Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, The National Academy Press, 456pp.

Cress, A. and W. Wergen, 2001:Impact of profile observations on the German Weather Service’s NWP system, Meteorologische Zeitschrift, 10, 91-101.

Deshpande, Medha,  P. Mukhopadhyay, Michiko Masutani,  Zaizhong Ma,  Lars Peter Riishojgaard,  Michael Hardesty, Dave Emmitt, T. N. Krishnamurti, B. N. Goswami, 2016;  Analysis and evaluation of Observing System Simulation Experiments (OSSEs) forecast data for Indian summer monsoon. Proc. SPIE 9882, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI, 98821P (May 3, 2016); doi:10.1117/12.2223656.

Desroziers, G. and S. Ivanov, 2001: Diagnosis and adaptive tuning of information error parameters in a variational assimilation. Quart. J. Roy. Meteor. Soc., 127, 1433-1452.

Emmitt, G. D. and S. A. Wood 1991: Simulating thin cirrus clouds in observing system simulation experiments (OSSE) for LAWS Proc. AMS Seventh Symp. on Meteorol. Observa. and Instru., Special Session on Laser Atmospheric Studies, New Orleans, LA, January 14-18, 460-462.

Errico, Ronald  et al 2006: The use of an OSSE to estimate characteristics of analysis error.  Presentation at EMC seminar


Errico, R.M., R. Yang, M. Masutani, M., and J. Woollen, 2007: The Estimation of Analysis Error Characteristics Using an Observation System Simulation Experiment, . Meteorologische Zeitschrift, 16, 695-708. DOI: 10.1127/0941-2948/2007/0242

Errico RM, Yang R, Prive NC, Tai K-S, Todling R, Sienkiewicz ME, Guo J. 2012. Development and validation of observing-system simulation experiments  at NASA’s Global Modeling and Assimilation Office. Q. J. R. Meteorol. Soc. DOI:10.1002/qj.2027

Errico, R. M. amd N. Prive, 2014: An estimate of some analysis-error statistics using the Global Modeling and Assimilation Office observing-system simulation framework, Q. J. R. Meteorol. Soc. 140: 1005–1012, DOI:10.1002/qj.2180

Fiolino, M 2008: Recent trends in dynamical medium-range tropical cyclone track prediction and the role of resolution versus physics in the ECMWF model.  Fiorino_tc.mrt.res.v.physics.ecmwf-1.pdf

Foelsche, U, Kirchengast, G., Steiner, A. K., Kornblueh, L., Manzini, E., and  Bengtsson, L 2008: An observing system simulation experiment for climate monitoring with GNSS radio occultation data: Setup and test bed study,  J. Geophys. Res. 113(D11108), , doi:10.1029/2007JD009231.

Frehlich, R. G.  and M. J. Kavaya, "Coherent laser radar performance for general atmospheric refractive turbulence," Appl. Opt. 30(36), 5325-5352 (1991)

Garand, L., J. Feng, S. Heilliette, Y. Rochon, 2013: Assimilation of Circumpolar Wind Vectors Derived from Highly Elliptical Orbit Imagery: Impact Assessment Based on Observing System Simulation Experiments, J. Appl. Meteor. Climatol.,52, 1891-1908. DOI: 10.1175/JAMC-D-12-0333.1

Gelaro R. and Y. Zhu 2008. Examination of observation impacts derived from observing system experiments (OSEs) and adjoint models. Tellus,  61A, 179-193.

Halem, H. and R. Dlouhy, 1984: Observing system simulation experiments related to space-borne lidar wind profiling. Part 1: Forecast impacts of highly idealized observing systems.  Preprints, Conference on Satellite Meteorology/ remote Sensing and Applications, Clearwater, Fla., Amer. Meteoro. Soc., 272-279.

Heilliette, S., Y. Rochon, L. Garand, and J. W. Kaminski, 2013: Assimilation of infrared radiances in the context of observing system simulated experiments. J. Appl. Meteor. Climatol., 52, 1031–1045.

Hill, C, P. J. Fitzpatrick, and V. Anantharaj, 2008: A Rapid Prototyping Capability Experiment to Evaluate CrIS/ATMS Observations for Urban Modeling Applications, Mississippi State Univ report.

Hoffman, R.N., C. Grassotti, R. G. Isaacs, J.-F. Louis, and T. Nehrkorn, 1990: Asessment of the Impact of Simulated Satellite Lidar Wind and Retrieved 183 GHz Water Vapor Observation of Global Data Assimilation System, Mon. Wea. Rev., 118, 2513-2542.

Hoffman, R. N. and R. Atlas, 2015: Future Observing System Simulation Experiments, Bull. Amer. Meteorol. Soc, Dec 2015, doihttp://dx.doi.org/10.1175/BAMS-D-15-00200.1

Jones, Andrew  S. 2008:What is Data Assimilation? A Tutorial, Presentation at AMS data assimilation forum.  AMS annual meeting, New Orleans, LA, January 20-24,2008


Jung, T. , A.M. Tompkins and M.J. Rodwell 2005:   Some aspects of systematic error in the ECMWF model. ECMWF Technical Memo No.471


Kalnay, E, Jusem, J C and J Pfaendtner, 1985. The relative importance of mass and wind data in the FGGE observing system.  Proceedings of the NASA Symposium on Global Wind Measurements, Clumbia, MD, NASA, 1-5.

Kavaya, M. J., R. G. Frehlich, 2007: Lidar and Mission Parameter Trade Study of Space-Based Coherent Wind Measurement Centered on NASA’s 2006 GWOS Wind Mission Study Parameters, Proceeding for 14th Coherent Laser Radar Conference, July 8-13, 2007, Snowmass, Colorado.

Kleist, Daryl T., David F. Parrish, John C. Derber, Russ Treadon, Wan-Shu Wu, Stephen Lord, 2009: Introduction of the GSI into the NCEP Global Data Assimilation System. Wea. Forecasting, 24, 1691–1705.

Kleist, D. T., and K. Ide, 2015a: An OSSE-based evaluation of hybrid variational-ensemble data assimilation for the NCEP GFS. Part I: System description and 3D-Hybrid results. Mon. Wea. Rev., 143 (2), 433–451, doi:10.1175/MWR-D-13-00351.1.

Kleist, D. T., and K. Ide, 2015b: An OSSE-based evaluation of hybrid variational-ensemble data assimilation for the NCEP GFS. Part II: 4DEnVar and hybrid variants. Mon. Wea. Rev., 143 (2), 452–470, doi:10.1175/MWR-D-13-00350.1.

Korb C., B. Gentry, and C. Y. Weng 1992: The Edge Technique - Theory and application to the Lidar Measurement of Atmospheric Winds. Applied Optics, 31, pp 4202-4212.

Lahoz, W.,  R. Brugge, D. R. Jackson, S. Migliorini, R. Swinbank, D. Lary, and A. Lee, 2005: An observing system simulation experiment to evaluate the scientific merit of wind and ozone measurements from the future SWIFT instrument, Quarterly Journal, Royal Meteorological Society, 131, 503-523.

Lahoz, William, Khattatov, Boris, Menard, Richard (Eds.)  2010: Data Assimilation, Making Sense of Observation..  Springer, 732 p., Hardcover ISBN: 978-3-540-74702-4


Liu, J., and E. Kalnay (2007), Simple Doppler Wind Lidar adaptive observation experiments with 3D-Var and an ensemble Kalman filter in a global primitive equations model, Geophys. Res. Lett., 34, L19808, doi:10.1029/2007GL030707.

Lorenc,A.C., Graham,R.J., Dharssi,I., MacPherson,B., Ingleby,N.B., Lunnon,R.W.,1992, Preparation for the use of a Doppler wind lidar information in meteorological assimilation systems, ESA-CR(P)-3454   http://www.emc.ncep.noaa.gov/research/osse/NR/references/Lorenc.1992.TIDCCR4129.pdf

Lorenc, A.C., 1986: Analysis methods for numerical weather prediction.  Quarterly Journal Royal Meteorological Society, 112, 1177-1194.

Lorenc, A.C. and O. Hammon, 1988: Objective quality control of observations using Bayesian methods: Theory, and a practical  implementationQuarterly Journal, Royal Meteorological Society, 114, 515--543.

Lord, S.J., E. Kalnay, R. Daley, G.D. Emmitt, R. Atlas, 1997: Using OSSEs in the
design of future generation integrated observing systems.  Preprints, 1st Symposium  on Integrated Observing Systems, Long Beach, CA, AMS, 45-47.


Lord, S.J., M. Masutani, J. S. Woollen, J.  C. Derber, R. Atlas,  J. Terry, G. D. Emmitt, S. A. Wood, S.  Greco, T. J. Kleespies, 2001a: Observing System Simulation Experiments for NPOESS, AMS Preprint volume the Fifth Symposium on Integrated Observing Systems.  14-19 January 2001, Albuquerque, NM 168-173.

Ma, Z., Riishojgaard, L.P., M. Masutani, J. S.Woollen,  and G. D. Emmitt, 2013: Impact of Different Satellite Wind Lidar Telescope Configurations on NCEP GFS Forecast Skill in Observing System Simulation Experiments, NCEP Office Note 475. available online at: Masutani, M, J. S. Woollen,S.J. Lord, T. J. Kleespies, G. D. Emmitt,  H. Sun,  S. A. Wood, S. Greco, J. Terry, R. Treadon, K. A. Campana 2006: Observing System Simulation Experiments at NCEP, NCEP Office note No.451. http://www.emc.ncep.noaa.gov/research/osse/NR/references/Masutani.2006.on451.pdf


Ma, Z.,L.-P.- Riishojgaard, M. Masutani, J. S. Woollen, G. D.  Emmitt, 2015: Impact of Different Satellite Wind Lidar Telescope Configurations on NCEP 1 GFS Forecast Skill in Observing System Simulation Experiments,  . J. Atmos. Oceanic Technol.32, 478–495.

Masutani, M, J. S. Woollen,S.J. Lord, T. J. Kleespies, G. D. Emmitt,  H. Sun,  S. A. Wood, S. Greco, J. Terry, R. Treadon, K. A. Campana 2006: Observing System Simulation Experiments at NCEP, NCEP Office note No.451. http://www.emc.ncep.noaa.gov/research/osse/NR/references/Masutani.2006.on451.pdf

Masutani, M. K. Campana, S. Lord, and S.-K. Yang 1999: Note on Cloud Cover of the  ECMWF nature run  used for OSSE/NPOESS project. NCEP Office Note No.427


Masutani, Michiko, Erik Andersson,  Joe Terry, Oreste Reale,  Juan Carlos Jusem, Lars Peter Riishojgaard, Tom Schlatter,  Ad Stoffelen,  Jack Woollen,   Steve Lord,   Zoltan TothYucheng Song,   Daryl Kleist,  Yuanfu Xie, Nikki Priv5,   Emily Liu, Haibing Sun,   Dave Emmit6,  Steve Greco,  Sid A. Wood,  Gert-Jan Marseille, Ron ErricoRunhua Yang, Gail  McConaughyDezso Devenyi,  Steve Weygandt, Adrian Tompkins, Thomas Jung, Valentine Anantharaj, Chris Hill, Pat Fitzpatrick,  Fuzhong Weng, Tong Zhu, Sid Boukabara 2007: Progress in Joint OSSEs, A new nature run and international collaboration, AMS preprint volume for 18th conference on Numerical Weather Prediction, Parkcity, UT Amer. Meteor. Soc. 12B.5,.


Masutani, M., T. W. Schlatter, R. M. Errico, A. Stoffelen, E. Andersson, W. Lahoz, J. S.. Woollen, G. D.Emmitt,L.-P. Riishøjgaard, S. J. Lord, 2010a: Observing System Simulation Experiments. Data Assimilation: Making sense of observations, Lahoz, W., B. Khattatov, R. Menard, Eds., Springer, 647-679.  Close to final draft is available at


Masutani, M, John S. Woollen, Stephen J. Lord, G. David Emmitt,  Thomas J. Kleespies, Sidney A. Wood, Steven Greco, Haibing Sun, Joseph Terry, Vaishali Kapoor, Russ Treadon, Kenneth A. Campana (2010), Observing system simulation experiments at the National Centers for Environmental Prediction, J. Geophys. Res., 115, D07101, doi:10.1029/2009JD012528. http://www.agu.org/pubs/crossref/2010/2009JD012528.shtml

Masutani, M. and co authrs 2011: Simulation of observation and calibrations for Joint OSSEs, Extended abstract, 15th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), Seattle, WA, Amer. Meteor. Soc. P199.

[Available online at  http://ams.confex.com/ams/91Annual/webprogram/Manuscript/Paper178667/Extended_Abstract_15IOS-AOLS-P199.pdf ]

Masutani, M., L. Garand, W. Lahoz, L.-P. Riishojgaard, E. Andersson, Y. Rochon, M. Tsyrulnikov, J. McConnell, L. Cucurull,  Y. Xie, S. Ishii, R. Grumbine, G. Brunet, J. S. Woollen, and Y. Sato, 2013: Observing System Simulation Experiments: Justifying new Arctic Observation Capabilities, White paper on OSSE Optimized Modelling, National Centers for Environmental Prediction Office Notes,  473. http://www.lib.ncep.noaa.gov/ncepofficenotes/files/on473.pdf

Masutani,M. 2016: Recent results and proposed observing system simulation experiments (OSSE) to link research and operation. Proc. SPIE 9882, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI, 98820A (May 3, 2016); doi:10.1117/12.2223930

Marseille, G.J., and A. Stoffelen 2003: “Simulation of wind profiles from a space-borne Doppler wind lidar, Q. J. R. Meteorol. Soc. 129, pp. 3079-3098.

Marseille, G.J., Stoffelen, A., Barkmeijer, J., 2006: Prediction Improvement of Extreme Weather (PIEW)   ESA contract report.


Marseille, G.J., Stoffelen, A., Barkmeijer J. , 2008a, Sensitivity Observing System Experiment (SOSE) - A New Effective NWP-based Tool in Designing the Global Observing System, Tellus, 60A, 216–233.

Marseille, G.J., Stoffelen, A., Barkmeijer J. , 2008b, Impact Assessment of Prospective Space-Borne Doppler Wind Lidar Observation Scenarios, Tellus, 60A, 234-248.

Marseille, G.J., Stoffelen, A., Barkmeijer J. , 2008c, A Cycled Sensitivity Observing System Experiment on Simulated Doppler Wind Lidar Data during the 1999 Christmas Storm "Martin" , Tellus, 60A, 249-260.

McCarty W, Errico RM, Gelaro R. 2012. Cloud coverage in the joint OSSE nature run. Mon. Weather Rev. 140: 1863–1871.

Nolan, D. S., R. Atlas, K. T. Bhetia, and L. R. Bucci, 2013: Development and validation of a hurricane nature run using the joint OSSE nature run and the WRF model, J. Adv. Modeling Earth Systems, 5, 382-404.

Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s Spectral Statistical-Interpolation Analysis System, Mon. Weather Rev., 120,  1747-1763.

Petersen, Daniel P.,1968:On the Concept and Implementation of Sequential Analysis for Linear Random Fields, Tellus, 20, 673-686

Prive, N., Y. Xie, T. W. Schlatter, M. Masutani, R. Atlas, Y. Song, J. Woollen, and S. Koch 2009: Observing System Simulation Experiments for Unmanned Aircraft Systems: preliminary efforts, Extended Abstract, 13th Conference on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface (IOAS-AOLS), Amer. Meteor. Soc, 13.3. [Available on line athttp://ams.confex.com/ams/pdfpapers/145313.pdf]

Prive N. C. , Errico R.M., Tai K-S. 2012. Validation of the forecast skill of the Global Modeling andAssimilation Office Observing System Simulation Experiment. Q. J. R. Meteorol. Soc. DOI:10.1002/qj.2029 

Prive,N., Y. Xie, J.S. Woollen, S. Koch, R. Atlas, and R. E. Hood, 2013: Evaluation of the Earth Systems Research Laboratory’s global Observing System Simulation Experiment system, Tellus A 65, 19011, http://dx.doi.org/10.3402/tellusa.v65i0.19011

Prive N. C.  and  R. M. Errico, 2013:The role of model and initial condition error in numerical weather forecasting investigated with an observing system simulation experiment .  Tellus A, 65, 21740, http://dx.doi.org/10.3402/tellusa.v65i0.21740

Prive, N. C., R.M. Errico and K.-S. Tai. 2013: The influence of observation errors on analysis error and forecast skill investigated with an observing system simulation experiment, J. Geophys. Res. Atmos., 118, 5332–5346, doi:10.1002/jgrd.50452.

Prive N. C. , R. M. Errico, and G. Wei, 2014: Use of an OSSE to evaluate background-error covariances estimated by the NMC method, Q. J. R. Meteorol. Soc. DOI:10.1002/qj.2384

Pu, Z., L. Zhang, and G. D. Emmitt, 2010: Impact of airborne Doppler Wind Lidar data on numerical simulation of a tropical cyclone , Geophy. Res. Lett., 37, L05801,doi:10.1029/2009GL041765.

Purser, R. J. 1984:  A new approach to the optimal assimilation of meteorological data by iterative Bayesian analysis.  AMS preprint volume. 10th conference on weather forecasting and analysis.  102-105.


Rabier, F.,P. Gauthier, C. Cardinali, R. Langland, M. Tsyrulnikov, A. Lorenc, P. Steinle, R. Gelaro, andK. Koizumi 2008:An update on THORPEX-related research in data assimilation andobserving strategies, Nonlin. Processes Geophys., 15, 81–94, 2008       www.nonlin-processes-geophys.net/15/81/2008/


Reale O., J. Terry, M. Masutani, E. Andersson, L. P. Riishojgaard, J. C. Jusem (2007), Preliminary evaluation of the European Centre for Medium-Range Weather Forecasts' (ECMWF) Nature Run over the tropical Atlantic and African monsoon region, Geophys. Res. Lett., 34, L22810, doi:10.1029/2007GL031640.


Riishojgaard, L. P., R. Atlas, and G. D. Emmitt, 2004: The impact of Doppler lidar wind observations on a single-level meteorological analysis. J. Appl. Meteor., 43, 810–820.

Riishojgaard, L.P., Z. Ma, M. Masutani, J. S.Woollen, G. D. Emmitt, S. A. Wood, and S. Greco, 2012: Observation System Simulation Experiments for a Global Wind Observing Sounder. Geophys. Res. Lett., 39, L17805, doi:10.1029/2012GL051814.

Rohaly, G. D. and T. N. Krishnamurti, 1993: An Observing System Simulation Eperiment for the Laser Atmospheric Wind Sounder (LAWS), Mon. Wea. Rev,32,1453-1472.

Seablom, M., S.J. Talabac, J. Ardizzone and J. Terry, 2008: A Sensor Web Simulator for Design of New Earth Science Observing Systems. IGARSS(5), 298-301.

Stoffelen Ad, Jean PailleuxbErland Källénc, J. Michael Vaughand, Lars Isaksene, Pierre Flamantf, Werner Wergeng, Erik Anderssonh, Harald Schybergi, Alain Culomaj, Roland Meynartj, Martin Endemannj, and Paul Ingmann 2005: The Atmospheric Dynamics Mission for Global Wind Field Measurement, submitted to Bull. American Met. Soc. 86,  73-87.

Stoffelen, A., G. J. Marseille, F. Bouttier, D. Vasiljevic, S. De Haan And C. Cardinali  2006:ADM-Aeolus Doppler wind lidar Observing System Simulation Experiment,  Quar.J.Roy. Metorol. Soc. , 619, 1927-1948

Tan, D.G.H., E. Andersson, M. Fisher and L. Isaksen 2007: Observing system impact assessment using a data assimilation ensemble technique: application to the ADM-Aeolus wind profiling mission .  ECMWF technical Memoranda 510

Tan, D.G.H., E. Andersson, M. Fisher and L. Isaksen 2007: Observing system impact assessment using a data assimilation ensemble technique: Application to the ADM-Aeolus wind profiling mission .  Q.J.Roy.Met.Soc, 133, 381-390.

Tompkins, A.M., P. Bechtold, A.C.M. Beljaars, A. Benedetti, S. Cheinet, M. Janisková, M. Köhler, P. Lopez, and J.-J. Morcrette 2004 :  Moist physical processes in the IFS: Progress and Plans . ECMWF Technical Memo No.452


Trichtchenko, L. D., L. V. Nikitina, A. P. Trishchenko, and L. Garand, 2014: Highly Elliptical Orbits for Arctic observations: Assessment of ionizing radiation, Advance in Space Research 54, 2398-2414.

Von Bremen, L.,N. Bormann, S. Wanzong, M. Hortal, D. Salmond, J.-N. Thepaut, and P. Bauer, 2008: Evaluation of AMVs Derived from ECMWF model Simulations, 9th International Winds Workshop, Annapolis, MD 14-18 April 2008.


Wood, S. A. G. D. Emmitt, and L. S. Wood, 1991: Global three-dimensional distribution of LAWS observations based upon aerosols, water vapor and clouds. Optical Remote Sensing of the Atmosphere, Fifth Topical Meeting, Williamsburg, VA, November 18-21.

Wood, S., G. Emmitt and S. Greco, 2000: DLSM: A coherent and direct detection lidar simulation model for simulating space-based and aircraft-based lidar winds.  Proceedings SPIE’s 14th Annual International Symposium Aerospace Defense Sensing, Simulation and Controls, Orlando, FL.

Woollen, J. S., M. Masutani, Y. Song, S. Toth, and G. D. Emmitt, 2006: Adaptive targeting OSSEs for planning a space-based Doppler Wind Lidar, AMS preprint volume for 10th IOAS-AOLS, Atlant, GA, 30 January-2 February, 2006, DOI: 10.13140/RG.2.1.1161.3609

Woollen, J. S., M. Masutani, H. Sun, Y. Song, G. D. Emmitt, Z. Toth, S. J. Lord, and Y. Xie 2008:  Observing Systems Simulation Experiments at NCEP,  OSSEs for realistic adaptive targeted DWL Uniform observation and AIRS. Extended abstract, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, New Orleans, LA, Amer. Meteor.Soc.. P1.7. [Available online at http://ams.confex.com/ams/pdfpapers/133682.pdf]

World Meteorological Organisation (WMO),2004: Proceedings of the ’Third WMO Workshop on the Impact of various observingsystems on Numerical Weather Prediction’,WMO/TD No 1228, 329p.

World Meteorological Organisation (WMO),  2002:Report of eighteenth session of the CAS/JSC Working Group on Numerical Experimentation, Météo-France, Toulouse, France, 18-22 October 2002 ,WMO/ TD-1173 (WGNE-18)

World Meteorological Organization 2008: Fourth WMO Workshop on the Impact of Various Observing Systems on NWP Geneva, Switzerland, 19-21 May 2008

Zhang, L. and Z. Pu, 2010: An Observing System Simulation Experiment (OSSE) to assess the impact of Doppler wind lidar (DWL) measurements on the numerical simulation of a tropical cyclone, Advances in Meteorology, Vol. 2010, Article ID 743863, 14pp, doi:10.1155/2010/743863

Zhu, Yanqiu and Ronald Gelaro, 2008: Observation Sensitivity Calculations Using the Adjoint of the Gridpoint Statistical Interpolation (GSI) Analysis System.  Mon. Wea. Rev.136, 335-351.

Zhu, T., F. Weng, M. Masutani, and J. S. Woollen, 2012: Synthetic radiance simulation and evaluation for a Joint Observing System Simulation Experiment, J. Geophys. Res., 117, D23111, doi:10.1029/2012JD017697