Dr. Daniel Holdaway

Dr. Daniel Holdaway

  • RSCH AST, EARTH SCIENCES REMOTE SENS
  • 301.614.6158 | 301.614.6246
  • NASA/GSFC
  • Mail Code: 610.1
  • Greenbelt , MD 20771
  • Employer: NASA
  • Brief Bio

    Daniel is an expert in data assimilation using the JEDI (Joint Effort for Data assimilation Integration) system. He currently works on implementing a coupled data assimilation system for use with GMAO's GEOS (Goddard Earth Observing System) model. In addition he oversees the development and adoption of a new workflow and infrastructure for cycling the JEDI-GEOS.


    Prior to joining the GMAO Daniel spent three and a half years working at the Joint Center for Satellite Data Assimilation (JCSDA) where he worked on several components of the JEDI system. He implemented an interface between JEDI and NASA's GEOS and NOAA's UFS forecast models. In addition he worked on many aspects of the JEDI system, including background error models, observation operators, forecast model adjoint development, variable transforms, infrastructure development, workflow and diagnostics.


    Prior to joining the JCSDA Daniel worked under GESTAR at NASA Goddard Space Flight Center. During this time he developed an adjoint version of the FV3 dynamical core and adjoint versions of several physics packages in GEOS. In addition to delivering a state of the art Forecast Sensitivity Observation Impact (FSOI) tool to operations at GMAO he worked on several interesting research questions. These included sudden stratospheric warming, the role of Saharan dust in tropical cytogenesis and the role of small errors in predictability of topical cyclone track and intensity.

     

    Positions/Employment

    9/2021 - Present

    Research Physical Scientist

    NASA, Goddard Space Flight Center

    Developing an Earth system coupled data assimilation model based on the Joint Effort for Data assimilation Integration (JEDI).

    10/2020 - 9/2021

    JEDI Project Lead for Model Interfaces

    Joint Center for Satellite Data Assimilation, Goddard Space Flight Center and UCAR

    Leading an Agile team of scientists and software engineers working to leverage the JEDI infrastructure for use with current and next generation numerical weather forecast models. Delivering major scientific and computation advancements for the JEDI data assimilation system. Coordinating with JCSDA partners to deliver operational grade data assimilation software.

    5/2018 - 10/2020

    Project Scientist II

    Joint Center for Satellite Data Assimilation, Goddard Space Flight Center and UCAR

    Leading the development of the interface between the Joint Effort for Data assimilation Integration (JEDI) and the NASA GEOS and NOAA GFS numerical forecast models. Coordinating with external partners, the Environmental Modeling Center and NASA's Global Modeling and Assimilation Office, to deliver tailored products, and plan the transition of research to operations. Overseeing staff working on software development and configuration implementation for conventional and satellite data, validation, workflow and research. Developing a 4DVar data assimilation system for use with GFS and GEOS. Optimization of high resolution data assimilation techniques, especially as it relates to background error covariance modeling, adjoint propagation and interpolation.

    12/2013 - 5/2018

    Scientist II

    University Space Research Association, Greenbelt, MD

    Developed the tangent linear and adjoint versions of the finite volume cubed-sphere (FV3) dynamical core, as well as the convection, cloud, boundary layer, radiation and chemistry schemes. Delivered a sophisticated forecast sensitivity observation (FSOI) impact tool to operations at NASA's Global Modeling and Assimilation Office. The FSOI tool is used to routinely monitor the global satellite and conventional observing system. Performed sensitivity studies using the GEOS adjoint to help understand the breakdown of the winter stratospheric polar vortex, examine how dust interacts with developing tropical cyclones, how small changes to steering wind can impact hurricane track and how concentrations of atmospheric constituents like CO2 are sensitive to their sources.

    2/2011 - 12/2013

    Scientist I

    University Space Research Association, Greenbelt, MD

    Developed novel techniques for the linearization of physical parameterizations. Delivered sophisticated adjoint version of a modern convection scheme.

    10/2010 - 2/2011

    Postdoctoral Researcher

    Exeter University and Tradewind Turbines, Exeter, United Kingdom

    Computational Fluid Dynamics (CFD) of local wind flow with a view to optimal wind turbine positioning.

    Education

    Degree of Ph.D. in Mathematics. Exeter University, 2010. “Coupling Large Scale Dynamics to the Planetary Boundary Layer: Impact of Vertical Discretisation”. Advised by Professor John Thuburn (Exeter University) and Dr. Nigel Wood (Met Office).

    Degree of M.Sc. in Computational Science and Modelling. Exeter University, 2006. Awarded with Distinction (First Class).

    Degree of B.Sc. in Mathematics. Exeter University, 2005. Awarded with upper second class honours, 2:1.

    Professional Societies

    American Meteorological Society, 2011 - Present

    Other Professional Information

    Google Scholar

    LinkedIn

    Publications

    Refereed

    Marquet, P., J.-F. Mahfouf, and D. Holdaway. 2020. "Definition of the Moist-Air Exergy Norm: A Comparison with Existing “Moist Energy Norms”." Monthly Weather Review, 148 (3): 907-928 [10.1175/mwr-d-19-0081.1]

    Delgado-Bonal, A., A. Marshak, Y. Yang, and D. Holdaway. 2020. "Analyzing changes in the complexity of climate in the last four decades using MERRA-2 radiation data." Scientific Reports, 10 (1): 922 [10.1038/s41598-020-57917-8]

    Reale, O., E. L. McGrath-Spangler, W. McCarty, D. Holdaway, and R. Gelaro. 2018. "Impact of adaptively thinned AIRS cloud-cleared radiances on tropical cyclone representation in a global data assimilation and forecast system." Weather and Forecasting, 33 (4): 908-931 [10.1175/waf-d-17-0175.1]

    Kent, J., and D. R. Holdaway. 2017. "An Idealised Test Case For Assessing The Linearization of Tracer Transport Schemes in NWP Models." Q. J. R. Meteorol. Soc., 143 (705): 1746–1755 [10.1002/qj.3027]

    Holdaway, D., and Y. Yang. 2016. "Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part II): Cloud Coverage." Remote Sensing, 8 (5): [10.3390/rs8050431]

    Holdaway, D., and Y. Yang. 2016. "Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earth’s Radiation Budget." Remote Sens., 8 (2): 98 [10.3390/rs8020098]

    Holdaway, D., R. M. Errico, R. Gelaro, J. G. Kim, and R. B. Mahajan. 2015. "A Linearized Prognostic Cloud Scheme in NASA’s Goddard Earth Observing System Data Assimilation Tools." Monthly Weather Review, 143 (10): 4198-4219 [10.1175/MWR-D-15-0037.1]

    Holdaway, D. R., and J. Kent. 2015. "Assessing the tangent linear behaviour of common tracer transport schemes and their use in a linearised atmospheric general circulation model ." Tellus A, 67: 27895 [10.3402/tellusa.v67.27895]

    Holdaway, D. R., and R. M. Errico. 2014. "Using Jacobian sensitivities to assess a linearization of the relaxed Arakawa-Schubert convection scheme." Q.J.R. Meteorol. Soc., 140 (681): 1319-1332 [10.1002/qj.2210]

    Holdaway, D. R., R. M. Errico, R. Gelaro, and J. G. Kim. 2014. "Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools." Mon. Weather Rev., 142 (1): 414-433 [10.1175/MWR-D-13-00193.1]

    Holdaway, D. R., J. Thuburn, and N. Wood. 2013. "Comparison of Lorenz and Charney–Phillips vertical discretisations for dynamics–boundary layer coupling. Part I: Steady states." Quarterly Journal of the Royal Meteorological Society, 139 (673): 1073-1086 [10.1002/qj.2016]

    Holdaway, D. R., J. Thuburn, and N. Wood. 2013. "Comparison of Lorenz and Charney–Phillips vertical discretisations for dynamics–boundary layer coupling. Part II: Transients." Quarterly Journal of the Royal Meteorological Society, 139 (673): 1087–1098 [10.1002/qj.2017]

    Holdaway, D. R., J. Thuburn, and N. Wood. 2007. "On the relation between order of accuracy, convergence rate and spectral slope for linear numerical methods applied to multiscale problems." International Journal for Numerical Methods in Fluids, 56 (8): 1297-1303 [10.1002/fld.1644]

    Talks, Presentations and Posters

    Invited

    Yonsei University Seminar Series

    5 / 13 / 2021
    • Towards the next generation data assimilation system for NASA’s GEOS model

    NASA Sciences and Exploration Directorate (600) Director's Seminar

    6 / 4 / 2019
    • Building the Data Assimilation System of the Future

    Winter School on the Influence of Diabatic Processes on Atmospheric Development, Bergen Norway

    3 / 2019
    • Data assimilation methods and challenges
    • Adjoint and Ensemble sensitivity
    • Forecast sensitivity to Observations Impacts

    JCSDA Summer Colloquium

    7 / 24 / 2018
    • Adjoint Basics

    Workshop on Sensitivity Analysis and Data Assimilation in Meteorology and Oceanography

    7 / 2 / 2018
    • Adjoint Basics
    • Progress towards hybrid 4DVar with the FV3 dynamical core

    Stony Brook University Seminar Series

    4 / 25 / 2018
    • The tangent linear and adjoint of the FV3 dynamical core: development and applications

    Naval Research Laboratory Invited Seminar

    5 / 17 / 2017
    • Development and applications of the FV3 GEOS-5 adjoint modeling system

    George Mason University Center for Ocean-Land-Atmosphere Studies

    3 / 1 / 2017
    • Examining predictability of weather forecasts using an adjoint

     GE Whitney Symposium

    10 / 12 / 2015
    •  Data assimilation and observation analysis for numerical weather prediction at NASA

     JCSDA Summer Colloquium

    8 / 4 / 2015
    •  Presented lecture on "Adjoint Model Basics"

    Other

    AMS Annual Meeting 2020

    1 / 12 / 2020
    • Toward Full-Resolution Cycled Data Assimilation with FV3-JEDI
    • Using Machine Learning to Derive Linearized Physical Parameterizations (Poster)

    JCSDA Workshop 2019

    5 / 29 / 2019
    • Progress Towards Hybrid-4DVar Data Assimilation with FV3-JEDI

    AMS Annual Meeting 2019

    1 / 2019
    • FV3-JEDI: Progress toward interfacing the GFS and GEOS weather forecast models with JEDI

    JCSDA Workshop (2018)

    5 / 31 / 2018

    FV3-JEDI: Progress Report and Future Plans

    AMS Annual Meeting 2018

    1 / 2018
    • Progress toward integrating the Finite-Volume Cubed-Sphere (FV3) dynamical core tangent linear and adjoint models into JEDI

    AMS Annual Meeting 2017

    1 / 23 / 2017
    • Forecast Sensitivity Observation Impact (FSOI) Inter-comparison Experiment (co-author)
    • Development and applications of the adjoint of the non-hydrostatic GEOS-5 FV3 dynamical core
    • Investigating the Source of Track and Intensity Errors in Forecasts of Hurricane Joaquin Using the NASA GEOS-5 and Navy Coamps Adjoint Systems

    AGU Fall Meeting 2016

    12 / 13 / 2016
    • Study of the effect of temporal sampling frequency on DSCOVR observations using the GEOS-5 Nature Run
    • Cloud Properties Of The Daytime Earth As Observed By DSCOVR-EPIC: A First Look

    32nd Conference on Hurricanes and Tropical Meteorology

    4 / 21 / 2016
    • Investigating Sensitivity to Saharan Dust During Hurricane Helene (2006) Using an Adjoint

    AMS Annual Meeting 2016

    1 / 14 / 2016
    • Investigating Sensitivity to Saharan Dust in Atlantic Hurricane Formation Using the GEOS-5 Adjoint Model
    • Assessment of the Current Satellite Observing System Using the GEOS-5 Observation Impact Monitoring Tool

    AGU Fall Meeting 2015

    12 / 16 / 2015
    • Investigating troposphere-stratosphere coupling during the southern hemisphere sudden stratospheric warming using an adjoint model.

     Goddard Young Scientist Forum

    7 / 15 / 2015
    • Investigating sensitivity to Saharan dust in tropical cyclone formation using the adjoint of GEOS-5

     Eurpoean Geosciences Union Annual Meeting

    4 / 13 / 2015
    • Investigating sensitivity to Saharan dust in tropical cyclone formation using NASA’s adjoint model.
    • Comparison of the tangent linear properties of tracer transport schemes applied to geophysical problems.

     Workshop on Meteorological Sensitivity Analysis and Data Assimilation

    1 / 6 / 2015
    •  Investigating sensitivity to dust in tropical cyclone formation using the GEOS-5 adjoint model

    Brief Bio

    Daniel is an expert in data assimilation using the JEDI (Joint Effort for Data assimilation Integration) system. He currently works on implementing a coupled data assimilation system for use with GMAO's GEOS (Goddard Earth Observing System) model. In addition he oversees the development and adoption of a new workflow and infrastructure for cycling the JEDI-GEOS.


    Prior to joining the GMAO Daniel spent three and a half years working at the Joint Center for Satellite Data Assimilation (JCSDA) where he worked on several components of the JEDI system. He implemented an interface between JEDI and NASA's GEOS and NOAA's UFS forecast models. In addition he worked on many aspects of the JEDI system, including background error models, observation operators, forecast model adjoint development, variable transforms, infrastructure development, workflow and diagnostics.


    Prior to joining the JCSDA Daniel worked under GESTAR at NASA Goddard Space Flight Center. During this time he developed an adjoint version of the FV3 dynamical core and adjoint versions of several physics packages in GEOS. In addition to delivering a state of the art Forecast Sensitivity Observation Impact (FSOI) tool to operations at GMAO he worked on several interesting research questions. These included sudden stratospheric warming, the role of Saharan dust in tropical cytogenesis and the role of small errors in predictability of topical cyclone track and intensity.

     

    Publications

    Refereed

    Marquet, P., J.-F. Mahfouf, and D. Holdaway. 2020. "Definition of the Moist-Air Exergy Norm: A Comparison with Existing “Moist Energy Norms”." Monthly Weather Review 148 (3): 907-928 [10.1175/mwr-d-19-0081.1]

    Delgado-Bonal, A., A. Marshak, Y. Yang, and D. Holdaway. 2020. "Analyzing changes in the complexity of climate in the last four decades using MERRA-2 radiation data." Scientific Reports 10 (1): 922 [10.1038/s41598-020-57917-8]

    Reale, O., E. L. McGrath-Spangler, W. McCarty, D. Holdaway, and R. Gelaro. 2018. "Impact of adaptively thinned AIRS cloud-cleared radiances on tropical cyclone representation in a global data assimilation and forecast system." Weather and Forecasting 33 (4): 908-931 [10.1175/waf-d-17-0175.1]

    Kent, J., and D. R. Holdaway. 2017. "An Idealised Test Case For Assessing The Linearization of Tracer Transport Schemes in NWP Models." Q. J. R. Meteorol. Soc. 143 (705): 1746–1755 [10.1002/qj.3027]

    Holdaway, D., and Y. Yang. 2016. "Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part II): Cloud Coverage." Remote Sensing 8 (5): [10.3390/rs8050431]

    Holdaway, D., and Y. Yang. 2016. "Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earth’s Radiation Budget." Remote Sens. 8 (2): 98 [10.3390/rs8020098]

    Holdaway, D., R. M. Errico, R. Gelaro, J. G. Kim, and R. B. Mahajan. 2015. "A Linearized Prognostic Cloud Scheme in NASA’s Goddard Earth Observing System Data Assimilation Tools." Monthly Weather Review 143 (10): 4198-4219 [10.1175/MWR-D-15-0037.1]

    Holdaway, D. R., and J. Kent. 2015. "Assessing the tangent linear behaviour of common tracer transport schemes and their use in a linearised atmospheric general circulation model ." Tellus A 67 27895 [10.3402/tellusa.v67.27895]

    Holdaway, D. R., and R. M. Errico. 2014. "Using Jacobian sensitivities to assess a linearization of the relaxed Arakawa-Schubert convection scheme." Q.J.R. Meteorol. Soc. 140 (681): 1319-1332 [10.1002/qj.2210]

    Holdaway, D. R., R. M. Errico, R. Gelaro, and J. G. Kim. 2014. "Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools." Mon. Weather Rev. 142 (1): 414-433 [10.1175/MWR-D-13-00193.1]

    Holdaway, D. R., J. Thuburn, and N. Wood. 2013. "Comparison of Lorenz and Charney–Phillips vertical discretisations for dynamics–boundary layer coupling. Part I: Steady states." Quarterly Journal of the Royal Meteorological Society 139 (673): 1073-1086 [10.1002/qj.2016]

    Holdaway, D. R., J. Thuburn, and N. Wood. 2013. "Comparison of Lorenz and Charney–Phillips vertical discretisations for dynamics–boundary layer coupling. Part II: Transients." Quarterly Journal of the Royal Meteorological Society 139 (673): 1087–1098 [10.1002/qj.2017]

    Holdaway, D. R., J. Thuburn, and N. Wood. 2007. "On the relation between order of accuracy, convergence rate and spectral slope for linear numerical methods applied to multiscale problems." International Journal for Numerical Methods in Fluids 56 (8): 1297-1303 [10.1002/fld.1644]

                                                                                                                                                                                            
    NASA Logo, National Aeronautics and Space Administration