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Derek Posselt

Scientist

About

Bio

Dr. Posselt is a research scientist with the Atmospheric Physics and Weather group (329E) in the Earth Science Section at NASA Jet Propulsion Laboratory (JPL), California Institute of Technology (Caltech). He is also a Project Scientist at the Joint Institute for Regional Earth System Science and Engineering (JIFRESSE) at the University of California, Los Angeles (UCLA).

Dr. Posselt has 20+ years of experience working on satellite data applications, the development of satellite missions, and confronting numerical models with remote sensing and in-situ observations. He served as NASA CYGNSS Deputy Principal Investigator from 2012 – 2016, and is currently the Deputy Project Scientist for the NASA INCUS mission. He is actively involved in the quantitative analysis of satellite information, including the use of uncertainty quantification (UQ) algorithms and observing system simulation experiments (OSSEs). He is also actively engaged in the development of new data assimilation and retrieval algorithms, particularly in a Bayesian probabilistic context.

Education

B.S., Atmospheric Science, University of Wisconsin, Madison, WI (1997)

M.S., Atmospheric Science, University of Wisconsin, Madison, WI (2001)

Ph.D., Atmospheric Science, Colorado State University, Fort Collins, CO (2006)

Research Interests

  • Cloud system sensitivity to changes in microphysics and environment
  • Data assimilation and remote sensing theory development
  • Cloud and precipitation property retrievals from active and passive remote sensing instruments
  • Quantitative assessment of information in current and future observing systems, including the design and use of observing system simulation experiments
  • Evaluation of model uncertainty, especially in the representation of moist processes
  • Cloud and precipitation processes in tropical convection, extratropical cyclones, and mountainous regions

Experience

Professional Experience

University of Michigan Climate and Space Sciences and Engineering, Associate Professor, 2014-2016

University of Michigan Atmospheric Oceanic and Space Sciences, Assistant Professor, 2011-2014

University of Michigan Atmospheric Oceanic and Space Sciences, Assistant Research Scientist, 2007-2011

Naval Research Laboratory - Monterey, Visiting Scientist, 2010-2011

Colorado State University Atmospheric Science Department, Post-doctoral Fellow, 2006-2007

Research Community Service

Editor, Monthly Weather Review (2021-Present)

Member, NOAA Environmental Information Systems Working Group (2023-Present)

NASA Langley Science Directorate Peer Review, Active Remote Sensing Sub-Panel Lead (2015)

Member, NASA Earth Science Senior Review Panel (2013,2015)

Achievements

Awards & Recognitions

  • NASA Award (2019)

Publications

  1. Naud, C.M., J. E. Martin, P. Ghosh, G. S. Elsaesser, J. F. Booth, and D. J. Posselt, 2025: Lifecycle-type Matters for Extratropical Cyclone Precipitation Production. Geophys. Res. Lett., 52, e2025GL115153. https://doi.org/10.1029/2025GL115153.
  2. Naud, C. M., G. S. Elsaesser, P. Ghosh, J. E. Martin, and D. J. Posselt, and J. F. Booth, 2025: How well does an Earth System Model represent the occlusion of extratropical cyclones? J. Climate, 38, pp. 1999-2014, https://doi.org/10.1175/JCLI-D-24-0252.1.
  3. Minamide, M., and D. J. Posselt, 2025: Improving Tropical Cyclone Intensification Prediction using High Resolution All-sky GOES Satellite Data Assimilation. Q. J. Roy. Met. Soc., http://dx.doi.org/10.1002/qj.4958
  4. Amiridis, V., E. Marinou, C. Hostetler, R. Koopman, D. Cecil, D. Moisseev, J. Tackett, et al. 2025: “Best Practice Protocol for the Validation of Aerosol, Cloud, and Precipitation Profiles (ACPPV)”. Zenodo, March 16, 2025. https://doi.org/10.5281/zenodo.15025627
  5. Schulte, R. M., R. J. Chase, B. Dolan, P. J. Marinescu, D. J. Posselt, K. L. Rasmussen, and S. C. van den Heever, 2024: Unclouding the Correlations: A Principal Component Analysis of Convective Environments. Geophys. Res. Lett., 51, https://doi.org/10.1029/2024GL111732.
  6. King, F., C. Pettersen, B. Dolan, J. Shates, and D. J. Posselt, 2024: Primary Modes of Northern Hemisphere Snowfall Particle Size Distributions. J. Atmos. Sci., 81, 2093-2113. https://doi.org/10.1175/JAS-D-24-0076.1.
  7. Freeman, S. W., D. J. Posselt, J. S. Reid, and S. C. van den Heever, 2024: Dynamic and Thermodynamic Environmental Modulation of Tropical Congestus and Cumulonimbus in Maritime Tropical Regions. J. Atmos. Sci., 81, 1921-1941. https://doi.org/10.1175/JAS-D-24-0055.1.
  8. Yanovsky, I., D. J. Posselt, L. Wu, and S. Hristova-Veleva, 2024: Quantifying Uncertainty in Atmospheric Winds Retrieved from Optical Flow: Dependence on Weather Regime. J. Appl. Meteor. Clim., 63, 1113-1135. https://doi.org/10.1175/JAMC-D-23-0169.1.
  9. Nguyen, H., D. J. Posselt, I. Yanovsky, L. Wu, and S. Hristova-Veleva, 2024: AMV Error Characterization and Bias Correction by Leveraging Independent Lidar Data: a Simulation using OSSE and Optical Flow AMVs. Atmos. Meas. Tech., 17, 3103-3119, https://doi.org/10.5194/amt-17-3103-2024.
  10. Naud, C. M., P. Ghosh, J. E. Martin, G. S. Elsaesser, and D. J. Posselt, 2024: A CloudSat-CALIPSO view of cloud and precipitation in the occluded quadrants of extratropical cyclones. Q. J. Roy. Meteor. Soc., 150, 1336-1356. https://doi.org/10.1002/qj.4648
  11. Takahashi, H., C. M. Naud, D. J. Posselt, and G. A. Duffy, 2024: Systematic Differences between the Northern and Southern Hemispheres: Warm-Frontal Ice Water Path Linked to the Origin of Extratropical Cyclones. J. Climate, 37, 2491-2504, https://doi.org/10.1175/JCLI-D-23-0391.1.
  12. Zeng, X., H. Su, S. Hristova-Veleva, D. J. Posselt, and co-authors, 2024: Vientos - A new satellite mission concept for 3D wind measurements by combining passive water vapor sounders with Doppler wind lidar. Bull. Amer. Meteor. Soc., 105, E357-E369. https://doi.org/10.1175/BAMS-D-22-0283.1
  13. Wu, L., H. Su; X. Zeng; D. J. Posselt; S. Wong; S. Chen; and A. Stoffelen, 2024: Uncertainty of Atmospheric Winds in Three Widely Used Global Reanalysis Datasets. J. Appl. Meteor. Clim., 63, 165-180, https://doi.org/10.1175/JAMC-D-22-0198.1.
  14. Yang, J. X., Y. You, W. Blackwell, C. Da, E. Kalnay, C. Grassotti, Q. Liu, R. Ferraro, H. Meng, C.-Z. Zou, S.-P. Ho, J. Yin, V. Petkovic, T. Hewison, D. Posselt, A. Gambacorta, D. Draper, S. Misra, R. Kroodsma, and Min Chen, 2024: SatERR: A Community Error Inventory for Satellite Observation Error Representation and Uncertainty Quantification. Bull. Amer. Meteor. Soc., 105, E1-E20, https://doi.org/10.1175/BAMS-D-22-0207.1.
  15. Matsui, T., D. B. Wolff, S. Lang, K. Mohr, M. Zhang, S. Xie, S. Tang, S. M. Saleeby, D. J. Posselt, S. A. Braun, J.-D. Chern, B. Dolan, J. L. Pippitt, and A. M. Loftus, 2023: Systematic Validation of Ensemble Cloud-Process Simulations using Polarimetric Radar Observations and Simulator over the NASA Wallops Flight Facility. J. Geophys. Res. Atmospheres. 128, https://doi.org/10.1029/2022JD038134.
  16. Naud, C. N., J. E. Martin, P. Ghosh, G. Elsaesser, and D. J. Posselt, 2023: Automated Identification of Occluded Sectors in Midlatitude Cyclones: Method and Some Climatological Applications. Q. J. Roy. Meteor. Soc., 149, 1990-2010. https://doi.org/10.1002/qj.4491.
  17. Naud, C. N., J. A. Crespo, D. J. Posselt, and J. F. Booth, 2023: Cloud and Precipitation in low-latitude extratropical cyclones conditionally sorted on CYGNSS surface latent and sensible heat fluxes. J. Climate, 36, 5659–5680, https://doi.org/10.1175/JCLI-D-22-0600.1.
  18. Asharaf, S., D. J. Posselt, F. Said, and C. S. Ruf, 2023: Updates on CYGNSS Ocean Surface Wind Validation in the Tropics. J. Atmos. Ocn. Tech., 40, 37-51. https://doi.org/10.1175/JTECH-D-21-0168.1
  19. Schultz, D. M., J. Anderson, T. Benacchio, K. L. Corbosiero, M. D. Eastin, C. Evans, J. Gao, J. P. Hacker, D. Hodyss, D. Kleist, M. R. Kumjian, R. McTaggart-Cowan, Z. Meng, J. Minder, D. Posselt, P. Roundy, A. Rowe, M. Scheuerer, R. S. Schumacher, S. Trier, and C. Weiss, 2022: Editorial: How to Be a More Effective Author. Mon. Wea. Rev., 150, 2819-2828.
  20. Xu, Z., G. G. Mace, and D. J. Posselt, 2022: Impact of Precipitation on Retrieved Warm Cloud Properties Using Visible and Near-infrared Reflectances Using Markov Chain Monte Carlo Techniques. IEEE Trans. Geosci. Rem. Sens., vol. 60, pp. 1-10, 2022, Art no. 4110110, https://doi.org/10.1109/TGRS.2022.3208007.
  21. da Silva AM, Kato S, Baker H, Redemann J, Posselt D, Ferrare R and Lebsock M (2022), Editorial: Remote sensing of cloud, aerosols, and radiation from satellites. Front. Remote Sens. 3:1040835. https://doi.org/10.3389/frsen.2022.1040835
  22. Park, H., J. Darko, N. Deshpande, V. Pandey, H. Su, M. Ono, D. Barkely, L. Folsom, D. Posselt, and S. Chien, 2022: Temporal Multimodal Multivariate Learning. In KDD ’22: ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 14–18, 2022, Washington DC. ACM, New York, NY, USA, 11 pages. https://doi.org/ 10.1145/3534678.3539159
  23. Duffy, G. A., and D. J. Posselt, 2022: A Gamma Parameterization for Precipitating Particle Size Distributions Containing Snowflake Aggregates Drawn from Five Field Experiments. J. Appl. Meteor. Clim., 61, 1077–1085. https://doi.org/10.1175/JAMC-D-21-0131.1
  24. Liu, Y., G. G. Mace, and D. J. Posselt, 2022: Assessing synergistic radar and radiometer retrievals of ice cloud microphysics for the Atmosphere Observing System (AOS) architecture. in IEEE Trans. Geophys. Rem. Sens., vol. 60, pp. 1-14, Art no. 4107714, doi: 10.1109/TGRS.2022.3165578.
  25. Vukicevic, T., D. J. Posselt, and A. Stankovich, 2022: Sensitivity of modeled microphysics to stochastically perturbed parameters. J. Adv. Modeling Earth Systems, 14, 20 pp. https://doi.org/10.1029/2021MS002933
  26. Minamide, M., and D. J. Posselt, 2022: Using Ensemble Data Assimilation to Explore the Environmental Controls on the Initiation and Predictability of Moist Convection, J. Atmos. Sci., 79, 1151–1169. https://doi.org/10.1175/JAS-D-21-0140.1
  27. Gettelman, A., A. J. Geer, R. M. Forbes, G. R. Carmichael, G. Feingold, D. J. Posselt, G. L. Stephens, S. C. van den Heever, A. C. Varble, and P. Zuidema, 2022: The future of Earth system prediction: Advances in model-data fusion. Science Advances, 8, 1-12, https://doi.org/10.1126/sciadv.abn3488
  28. Posselt, D. J., L. Wu, M. Schreier, J. Roman, M. Minamide, and B. Lambrigtsen, 2022: Assessing the Forecast Impact of a Geostationary Microwave Sounder using Regional and Global OSSEs. Mon. Wea. Rev., 150, 625-645. https://doi.org/10.1175/MWR-D-21-0192.1
  29. Natraj, V., M. Luo, J.-F. Blavier, V. Payne, J. Neu, Z. Zeng, S. Kulawik, L. Wu, J. Roman, D. J. Posselt, S. Sander, Y.-H. Wu, and L. Dorsky 2022: Simulated Multispectral Temperature and Atmospheric Composition Retrievals for the GEO-IR Sounder. Atmos. Meas. Tech., 15, 1251-1267. https://doi.org/10.5194/amt-15-1251-2022
  30. Grant, L. D., S. C. van den Heever, Z. S. Haddad, J. Bukowski, P. J. Marinescu, R. L. Storer, D. J. Posselt, and G. L. Stephens, 2022: A linear relationship between vertical velocity and microphysical process rates in deep convection. J. Atmos. Sci., 79, 449-466. https://doi.org/10.1175/JAS-D-21-0035.1
  31. Ouyed, A., X. Zeng, L. Wu, D. J. Posselt, and H. Su, 2021: Two Stage Artificial Intelligence Algorithm for Calculating Moisture-Tracking Atmospheric Motion Vectors. J. Appl. Meteor. Clim., 60, 1671–1684. https://doi.org/10.1175/JAMC-D-21-0070.1
  32. Lambrigtsen, B., P. Kangaslahta, O. Montes, N. Niamsuwan, D. J. Posselt, J. Roman, M. Schreier, A. Tanner, L. Wu, and I. Yanovsky, 2021: A Geostationary Microwave Sounder: Design, Implementation and Performance. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 623-640, 2022, doi: 10.1109/JSTARS.2021.3132238.
  33. Naud, C. M., J. A. Crespo, and D. J. Posselt, 2021: On the relationship between CYGNSS surface heat fluxes and the lifecycle of low-latitude extratropical cyclones. J. Appl. Meteor. Clim. 60, 1575-1590. https://doi.org/10.1175/JAMC-D-21-0074.1
  34. Posselt, D. J., B. D. Wilson, R. L. Storer, D. Tropf, G. A. Duffy, M. Lebsock, V. Lall, N. Niamsuwan, and S. Tanelli, 2021: A Science-Focused, Scalable, Flexible Observing System Simulation Experiment (OSSE) Toolkit, 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
  35. Lunderman, S., M. Morzfeld, and D. J. Posselt, 2021: Using global Bayesian optimization in ensemble data assimilation: parameter estimation, tuning localization and inflation, or all of the above. Tellus A: Dynamic Meteorology and Oceanography, 73:1, 1-16, doi:10.1080/16000870.2021.1924952.
  36. Crespo, J. A., C. M. Naud, and D. J. Posselt, 2021: CYGNSS Observations and Analysis of Low-Latitude Extratropical Cyclones. J. Appl. Meteor. Clim., 60, 527-541. https://doi.org/10.1175/JAMC-D-20-0190.1
  37. Asharaf, S., D. E. Waliser, D. J. Posselt, C. S. Ruf, C. Zhang, and A. W. Putra, 2021: CYGNSS Ocean Surface Wind Validation in the Tropics. J. Atmos. Ocn. Tech. 38, 711-724, https://doi.org/10.1175/JTECH-D-20-0079.1.
  38. Teixeira, J., H. Nguyen, D. J. Posselt, H. Su, and L. Wu, 2021: Using machine learning to model uncertainty for water vapor atmospheric motion vectors. Atmos. Meas. Tech., 14, 1941-1957. https://doi.org/10.5194/amt-14-1941-2021
  39. Morales, A., D. J. Posselt, and H. Morrison, 2021: Which combinations of environmental conditions and microphysical parameter values produce a given orographic precipitation distribution? J. Atmos. Sci., 78, 619-638. https://doi.org/10.1175/JAS-D-20-0142.1
  40. Suselj, K., D. J. Posselt, M. Smalley, M. Lebsock, and J. Teixeira, 2020: A new methodology for observation-based parameterization development. Mon. Wea. Rev., 148, 4159–4184. https://doi.org/10.1175/MWR-D-20-0114.1
  41. Maahn, M., D. D. Turner, U. Lohnert, D. J. Posselt, K. Ebell, G. G. Mace, and J. M. Comstock, 2020: Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know. Bull. Amer. Meteor. Soc., 101, E1512–E1523, https://doi.org/10.1175/BAMS-D-19-0027.1
  42. Zeng, X., R. Atlas, R. J. Birk, F. H. Carr, M. J. Carrier, L. Cucurull, W. H. Hooke, E. Kalnay, R. Murtugudde, D. J. Posselt, J. L. Russell, D. P. Tyndall, R. A. Weller, and F. Zhang, 2020: Use of Observing System Simulation Experiments in the U.S. Bull. Amer. Meteor. Soc., 101, E1427–E1438. https://doi.org/10.1175/BAMS-D-19-0155.1
  43. Morrison, H., M. van Lier-Walqui, A. M. Fridlind, W. W. Grabowski, J. Y. Harrington, C. Hoose, A. Korolev, M. R. Kumjian, J. A. Milbrandt, H. Pawlowska, D. J. Posselt, O. P. Prat, K. J. Reimel, S.-I. Shima, B. van Diedenhoven, and L. Xue, 2020: Confronting the challenge of modeling cloud and precipitation microphysics. J. Adv. Model. Earth. Sys., 12. https://doi.org/10.1029/2019MS001689
  44. Stephens, G., A. Freeman, E. Richard, P. Pilewskie, P. Larkin, C. Chew, S. Tanelli, S. Brown, D. J. Posselt, and E. Peral, 2020: The Emerging Technological Revolution in Earth Observations. Bull. Amer. Meteor. Soc., 101, E274–E285, https://doi.org/10.1175/BAMS-D-19-0146.1
  45. Stephens, G. L., S. C. van den Heever, Z. S. Haddad, D. J. Posselt, R. L. Storer, L. D. Grant, O. O. Sy, T. N. Rao, S. Tanelli, and E. Peral, 2020: A Distributed Small Satellite Approach for Measuring Convective Transports in the Earth’s Atmosphere. IEEE Trans. Geosci. Rem. Sens., 58, 4-13. doi:10.1109/TGRS.2019.2918090.
  46. Xu, Z., G. G. Mace, and D. J. Posselt, 2019: A method for assessing relative skill in retrieving cloud and precipitation properties in next generation cloud radar and radiometer orbiting observatories. J. Atmos. Ocn. Tech., 36, 2283–2306, https://doi.org/10.1175/JTECH-D-18-0204.1
  47. Storer, R. L., and D. J. Posselt, 2019: Environmental Impacts on the Flux of Mass Through Deep Convection. Q. J. Roy. Meteor. Soc., 145, 3832-3845. https://doi.org/10.1002/qj.3669.
  48. Posselt, D. J., L. Wu, K. Mueller, L. Huang, F. W. Irion, S. Brown, H. Su, D. Santek, and C. S. Velden, 2019: Quantitative Assessment of State-Dependent Atmospheric Motion Vector Uncertainties. J. Appl. Meteor. Climatol., 58, 2479–2495, https://doi.org/10.1175/JAMC-D-19-0166.1.
  49. Tierney, G. T., D. J. Posselt, and J. F. Booth, 2019: The Impact of Coriolis Approximations on the Environmental Sensitivity of Idealized Extratropical Cyclones. Clim. Dyn., 53, 7065-7080. https://doi.org/10.1007/s00382-019-04976-x
  50. Crespo, J. A., D. J. Posselt, and S. Asharaf, 2019: CYGNSS Surface Heat Flux Product Development. Rem. Sens., 11(19), 2294; https://doi.org/10.3390/rs11192294.
  51. Ruf, C., D. McKague, M. Morris, D. J. Posselt and M. Moghaddam, 2019: The GNSS-R Cygnss Mission: an Update, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 5171-5172, doi: 10.1109/IGARSS.2019.8900604.
  52. Reid. J. S., D. J. Posselt, K. Kaku, R. E. Holz, G. Chen, E. Eloranta, J. Jimenez, R. Kuehn, S. Woods, J. Zhang, B. Anderson. T. P. Bui, G. Diskin, P. Minnis, M. J. Newchurch, S. Tanelli, C. Trepte, K. Thornhill, and L. D. Ziemba, 2019: Observations and hypotheses related to low to middle free tropospheric aerosol, water vapor and altocumulus cloud layers within convective weather regimes: A SEAC4RS case study. Atmos. Chem. Phys., 19, 11413-11442. https://doi.org/10.5194/acp-19-11413-2019.
  53. Morales, A. M., D. J. Posselt, H. Morrison, and F. He, 2019: Assessing the Influence of Microphysical and Environmental Parameter Perturbations on Orographic Precipitation. J. Atmos. Sci., 76, 1373–1395, https://doi.org/10.1175/JAS-D-18-0301.1
  54. Pulido, M., P. van Leeuwen, and D. J. Posselt, 2019: Kernel embedded nonlinear observational mappings in the variational mapping particle filter, arXiv, http://arxiv.org/abs/1901.10426 [stat.ML]
  55. Posselt, D. J., F. He, J. Bukowski, and J.S. Reid, 2019: On the Relative Sensitivity of a Tropical Deep Convective Storm to Changes in Environment and Cloud Microphysical Parameters. J. Atmos. Sci., 76, 1163–1185, https://doi.org/10.1175/JAS-D-18-0181.1
  56. Tao, W.-K., J. Chern, T. Iguchi, S. Lang, M.-J. Lee, X. Li, A. Loftus, T. Matsui, K. Mohr, S. Nicholls, C. Peters-Lidar, D. J. Posselt, and G. Skofronick-Jackson, 2019: Microphysics in Goddard Multi-scale Modeling Systems: A Review. In “Current trend in the Representation of Physical Processes in Weather and Climate Models” by Springer Nature, 253-316 (2 February 2019).
  57. van den Heever, S. C., L. D. Grant, G. L. Stephens, Z. Haddad, R. L. Storer, O. O. Sy, and D. J. Posselt, 2018: The challenge of representing vertical motion in numerical models. Proc. SPIE 10782, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VII, 1078204 (23 October 2018); doi: 10.1117/12.2501584
  58. Haddad, Z. S., O. O. Sy, G. L. Stephens, S. C. van den Heever, and D. J. Posselt, 2018: Atmospheric remote sensing with convoys of miniature radars. Proc. SPIE 10776, Remote Sensing of the Atmosphere, Clouds, and Precipitation VII, 1077601 (2018); doi: 10.1117/12.2500285
  59. Posselt, D. J. and C. H. Bishop, 2018: Nonlinear Data Assimilation for Clouds and Precipitation using a Gamma-Inverse Gamma Ensemble Filter. Q. J. Roy. Meteor. Soc., 144, 2331-2349. https://doi.org/10.1002/qj.3374
  60. Ross, A., R. E. Holz, G. Quinn, J. S. Reid, P. Xian, F. J. Turk, and D. J. Posselt, 2018: Exploring the First Aerosol Indirect Effect over the Maritime Continent Using a 10-Year Collocated MODIS, CALIOP, and Model Dataset. Atmos. Chem. Phys., 18, 12747-12764, https://doi.org/10.5194/acp-18-12747-2018
  61. He, F., D. J. Posselt, N. N. Narisetty, C. M. Zarzycki, and V. N. Nair, 2018: Application of Multivariate Sensitivity Analysis Techniques to AGCM-Simulated Tropical Cyclones. Mon. Wea. Rev., 146, 2065-2088, doi: https://doi.org/10.1175/MWR-D-17-0265.1.
  62. Morales, A., H. Morrison, and D. J. Posselt, 2018: Orographic Precipitation Response to Microphysical Parameter Perturbations for Idealized Moist Nearly Neutral Flow. J. Atmos. Sci., 75, 1933-1953, https://doi.org/10.1175/JAS-D-17-0389.1
  63. Tierney, G., D. J. Posselt, and J. F. Booth, 2018: An Examination of Extratropical Cyclone Response to Changes in Baroclinicity and Temperature in an Idealized Environment. Cli. Dyn., 50, doi:https://doi.org/10.1007/s00382-018-4115-5.
  64. Naud, C. M., D. J. Posselt, and S. C. van den Heever, 2018: Reply to “Comments on ‘A CloudSat-CALIPSO view of cloud and precipitation properties across cold fronts over the global oceans’”. J. Climate, 31, 2969–2975, https://doi.org/10.1175/JCLI-D-17-0777.1
  65. Naud, C. M., D. J. Posselt, and S. C. van den Heever, 2017: Observed co-variations of aerosol optical depth and cloud cover in extratropical cyclones. J. Geophys. Res., 122, 10,338-10,356. doi:10.1002/2017JD027240.
  66. Crespo, J. A., D. J. Posselt, C. M. Naud, and C. Bussy-Virat, 2017: Assessing CYGNSS’s Potential to Observe Extratropical Fronts and Cyclones. J. Appl. Meteor. Clim., 56, 2027-2034.
  67. Ge, C., J. Wang, J. S. Reid, D. J. Posselt, P. Xian, and E. Hyer, 2017: Mesoscale modelling of smoke transport from equatorial Southeast Asian Maritime Continent to the Philippines: first comparison of ensemble analysis with in situ observations. J. Geophys. Res., 122, 5380–5398, doi:10.1002/2016JD026241.
  68. Roesler, E. L., D. J. Posselt, and R. B. Rood, 2017: Using large eddy simulations to reveal the size, strength, and phase of updraft and downdraft cores of an Arctic mixed phase stratocumulus cloud. J. Geophys. Res., 122, doi:10.1002/2016JD026055.
  69. Reid, J. S., R. E. Kuehen, R. E. Holz, E. W. Eloranta, K. C. Kaku, S. Kuang, M. J. Newchurch, A. M. Thompson, C. R. Trepte, J. Zhang, S. A. Atwood, J. L. Hand, B. N. Holben, P. Minnis, and D. J. Posselt, 2017: Ground based high spectral resolution lidar observation of aerosol vertical distribution in the summertime Southestern United States. J. Geophys. Res., 122, 2970–3004, doi:10.1002/2016JD025798
  70. Bukowski, J., D. J. Posselt, J. S. Reid, and S. A. Atwood, 2017: Modes of Thermodynamic and Wind Variability over the Maritime Continent. Atmos. Chem. Phys., 17, 4611-4626, doi:10.5194/acp-17-4611-2017.
  71. Posselt, D. J., J. Kessler, and G. G. Mace, 2017: Bayesian retrievals of vertically resolved cloud particle size distribution properties. J. Appl. Meteor. Clim., 56, 745-765, https://doi.org/10.1175/JAMC-D-16-0276.1
  72. Zhang, S., Z. Pu, D. J. Posselt, and R. Atlas, 2017: Impact of CYGNSS ocean surface wind speeds on numerical simulations of a hurricane in observing system simulation experiments. J. Atmos. Ocn. Tech., 34, 375-383, doi:10.1175/JTECH-D-16-0144.1.
  73. Li, X., J. R. Mecikalski, and D. J. Posselt, 2017: An Ice-Phase Microphysics Forward Model and Preliminary Results of Polarimetric Radar Data Assimilation. Mon. Wea. Rev., 145, 683-708, doi: 10.1175/MWR-D-16-0035.1.
  74. Reid, J. S., P. Xian, B. N. Holben, E. J. Hyer, E. A. Reid, S. V. Salinas, J. Zhang, J. R. Campbell, B. N. Chew, R. E. Holz, A. P. Kuciauskas, N. Lagrosas, D. J. Posselt, C. R. Sampson, A. L. Walker, E. J. Welton, and C. Zhang, 2016: Aerosol meteorology of the Maritime Continent for the 2012 7SEAS southwest monsoon intensive study – Part 1: regional-scale phenomena, Atmos. Chem. Phys., 16, 14041-14056, doi:10.5194/acp-16-14041-2016.
  75. Reid, J. S., N. D. Lagrosas, H. H. Jonsson, E. A. Reid, S. A. Atwood, T. J. Boyd, V. P. Ghate, P. Xian, D. J. Posselt, J. B. Simpas, S. N. Uy, K. Zaiger, D. R. Blake, A. Bucholtz, J. R. Campbell, B. N. Chew, S. S. Cliff, B. N. Holben, R. E. Holz, E. J. Hyer, S. M. Kreidenweis, A. P. Kuciauskas, S. Lolli, M. Oo, K. D. Perry, S. V. Salinas, W. R. Sessions, A. Smirnov, A. L. Walker, Q. Wang, L. Yu, J. Zhang, and Y. Zhao, 2016: Aerosol meteorology of Maritime Continent for the 2012 7SEAS southwest monsoon intensive study – Part 2: Philippine receptor observations of fine-scale aerosol behavior, Atmos. Chem. Phys., 16, 14057-14078, doi:10.5194/acp-16-14057-2016.
  76. Naud, C. M., D. J. Posselt, and S. C. van den Heever, 2016: Aerosol Optical Depth Distribution in Extratropical Cyclones over the Northern Hemisphere Oceans. Geophys. Res. Lett., 43, 10,504-10,511, doi:10.1002/2016GL070953.
  77. Crespo, J. A., and D. J. Posselt, 2016: A-Train Based Case Study of Stratiform - Convective Transition within a Warm Conveyor Belt, Mon. Wea. Rev., 144, 2069–2084. https://doi.org/10.1175/MWR-D-15-0435.1
  78. Ruf, C., R. Atlas, P. Chang, M. P. Clarizia, J. Garrison, S. Gleason, S. Katzberg, Z. Jelenak, J. Johnson, S. Majumdar, A. O’Brien, D. J. Posselt, A. Ridley, R. Rose, and V. Zavorotny, 2016: New Ocean Winds Satellite Mission to Probe Hurricanes and Tropical Convection. Bull. Amer. Meteor. Soc., 97, 385-395.
  79. van Lier-Walqui, M., A. M. Fridland, A. S. Ackerman, S. Collis, J. Helmus, D. R. MacGorman, K. North, P. Kollias, and D. J. Posselt, 2016: On Polarimetric Radar Signatures of Deep Convection for Model Evaluation: Columns of Specific Differential Phase Observed during MC3E. Mon. Wea. Rev., 144, 737-758.
  80. Posselt, D. J., 2016: A Bayesian Examination of Deep Convective Squall Line Sensitivity to Changes in Cloud Microphysical Parameters. J. Atmos. Sci., 73, 637–665.
  81. Posselt, D. J., B. Fryxell, A. Molod, and B. Williams, 2016: Quantitative Sensitivity Analysis of Physical Parameterizations for Cases of Deep Convection in the NASA GEOS-5 Model. J. Climate, 29, 455-479.
  82. He, F., and D. J. Posselt, 2015: Impact of Parameterized Physical Processes on Simulated Tropical Cyclone Characteristics in the Community Atmosphere Model. J. Climate, 24, 9857-9872.
  83. Tushaus, S. A., D. J. Posselt, M. M. Miglietta, R. Rotunno, and L. Delle Monache, 2015: Bayesian Exploration of Multivariate Orographic Precipitation Sensitivity for Moist Stable and Neutral Flows. Mon. Wea. Rev., 143, 4459-4475.
  84. Naud, C. M., D. J. Posselt, and S. C. van den Heever, 2015: A CloudSat-CALIPSO View of Cloud and Precipitation Properties Across Cold Fronts Over the Global Oceans. J. Climate, 28, 6743-6762. https://doi.org/10.1175/JCLI-D-15-0052.1
  85. Posselt, D. J., X. Li, S. A. Tushaus, and J. R. Mecikalski, 2015: Assimilation of Dual-Polarization Radar Observations in Mixed- and Ice- Phase Regions of Convective Storms: Information Content and Forward Model Errors. Mon. Wea. Rev., 143, 2611-2636.
  86. He, F., D. J. Posselt, C. M. Zarzycki, and C. Jablonowski, 2015: A Balanced Tropical Cyclone Test Case for AGCMs with Background Vertical Wind Shear. Mon. Wea. Rev., 143, 1762–1781.
  87. Bryan, A. M., A. L. Steiner, and D. J. Posselt, 2015: Regional modeling of surface-atmosphere interactions and their impact on Great Lakes hydroclimate. J. Geophys. Res., 120,1044-1064, DOI: 10.1002/2014JD022316.
  88. Reid, J. S., N. D. Lagrosas, H, H. Jonsson, E. A. Reid, W. R. Sessions, J. B. Simpas, S. N. Uy, T. J. Boyd, S. A. Atwood, D. R. Blake, J. R. Campbell, S. S. Cliff, B. N. Holben, R. E. Holz, E. J. Hyer, P. Lynch, S. Meinardi, D. J. Posselt, K. A. Richardson, S. V. Salinas, A. Smirnov, Q. Wang, L. E. Yu, and J. Zhang, 2015: Observations of the temporal variability in aerosol properties and their relationships to meteorology in the summer monsoonal South China Sea/East Sea: the role of monsoonal flows, the Madden–Julian Oscillation, tropical cyclones, squall lines and cold pools, Atmos. Chem. Phys., 15, 1745-1768, doi:10.5194/acp-15-1745-2015.
  89. Posselt, D. J., and G. G. Mace, 2014: MCMC-Based Assessment of the Error Characteristics of a Surface-Based Combined Radar–Passive Microwave Cloud Property Retrieval. J. Appl. Meteor. Clim., 53, 2034-2057.
  90. Tao, W.-K., S. Lang, X. Zeng, X. Li, T. Matsui, K. Mohr, D. J. Posselt, J. Chern, P. N. Norris, I.-S. Kang, I. Choi, and Y.-M. Yang, 2014: The Goddard Cumulus Ensemble (GCE) Model: Improvements and applications for Studying Precipitation Processes. Atmos. Res., 143, 392-424.
  91. Posselt, D. J., D. Hodyss, and C. H. Bishop, 2014: Errors in Ensemble Kalman Smoother Estimates of Cloud Microphysical Parameters, Mon. Wea. Rev., 142, 1631-1654.
  92. Igel, M. R., S. C. van den Heever, G. L. Stephens, and D. J. Posselt, 2014: Convective-Scale Responses Over a Large-Domain, Modeled Tropical Environment to Surface Warming, Q. J. Roy. Meteor. Soc., 140, 1333-1343.
  93. Lee, S.-S., B.-G. Kim, C. Lee, S.-S. Yum, and D. J. Posselt, 2014: Effect of aerosol pollution on clouds and its dependence on precipitation intensity. Cli. Dyn., 42, 557-577.
  94. van Lier-Walqui, M. A., T. Vukicevic, and D. J. Posselt, 2014: Linearization of microphysical parameterization uncertainty using multiplicative process perturbation parameters, Mon. Wea. Rev., 142, 401-413.
  95. Naud, C. M., J. F. Booth, D. J. Posselt, and S. C. van den Heever, 2013: Multiple satellite observations of cloud cover in extratropical cyclones, J. Geophys. Res., 118, 9982-9996. https://doi.org/10.1002/jgrd.50718
  96. Michalak, A.M., E.J. Anderson, D. Beletsky, S. Boland, N.S. Bosch, T.B. Bridgeman, J.D. Chaffin, K.H. Cho, R. Confesor, I. Daloğlu, J. DePinto, M.A. Evans, G.L. Fahnenstiel, L. He, J. C. Ho, L. Jenkins, T. Johengen, K.C. Kuo, E. LaPorte, X. Liu, M. McWilliams, M. R. Moore, D. J. Posselt, R.P. Richards, D. Scavia, A. L. Steiner, E. Verhamme, D. M. Wright, M.A. Zagorski, 2013: Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions. Proc. Nat. Acad. Sci., 110, 6448-6452.
  97. Igel, A. L, S. C. van den Heever, C. M. Naud, S. M. Saleeby, and D. J. Posselt, 2013: Sensitivity of warm frontal processes to cloud-nucleating aerosol concentrations. J. Atmos. Sci., 70, 1768-1783.
  98. Posselt, D. J., 2013: Markov chain Monte Carlo Methods: Theory and Applications. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, 2nd Ed. S. K. Park and L. Xu, Eds., Springer, pp 59–87.
  99. Wright, D. M., D. J. Posselt, and A. L. Steiner, 2013: Sensitivity of Lake-Effect Snowfall to Lake Ice Cover and Temperature in the Great Lakes Region. Mon. Wea. Rev., 141, 670-689.
  100. van Lier-Walqui, M., T. Vukicevic, and D. J. Posselt, 2012: Quantification of Cloud Microphysical Parameterization Uncertainty using Radar Reflectivity, Mon. Wea. Rev., 140, 3442-3466.
  101. Posselt, D. J., A. R. Jongeward, C.-Y. Hsu, and G. L. Potter, 2012: Object-Based Evaluation of MERRA-Simulated Cloud Physical Properties and Radiative Fluxes during the 1998 El Nino - La Nina Transition. J. Climate, 25, 7313-7327.
  102. Naud, C. M., D. J. Posselt, and S. C. van den Heever, 2012: Observational analysis of cloud and precipitation in midlatitude cyclones: northern versus southern hemisphere warm fronts. J. Climate, 25, 5135-5151. https://doi.org/10.1175/JCLI-D-11-00569.1
  103. Posselt, D. J., and C. H. Bishop, 2012: Nonlinear parameter estimation: Comparison of an Ensemble Kalman Smoother with a Markov chain Monte Carlo algorithm. Mon. Wea. Rev., 140, 1957-1974.
  104. Posselt, D. J., S. C. van den Heever, G. L. Stephens, and M. R. Igel, 2012: Changes in the interaction between tropical convection, radiation and the large scale circulation in a warming environment. J. Climate, 35, 557-571.
  105. Posselt, D. J., and T. Vukicevic, 2010: Robust Characterization of Model Physics Uncertainty for Simulations of Deep Moist Convection. Mon. Wea. Rev., 138, 1513–1535.
  106. Posselt, D. J., S. C. van den Heever, and G. L. Stephens, 2008: Trimodal cloudiness and tropical stable layers in simulations of radiative convective equilibrium. Geophys. Res. Lett., 35, L08802, doi:10.1029/2007GL033029.
  107. Posselt, D. J., G. L. Stephens, and M. Miller, 2008: CloudSat: Adding a New Dimension to a Classical View of Extratropical Cyclones. Bull. Amer. Meteor. Soc., 89, 599-609.
  108. Posselt, D. J., T. S. L’Ecuyer, and G. L. Stephens, 2008: Exploring the Error Characteristics of Thin Ice Cloud Property Retrievals Using a Markov Chain Monte Carlo Algorithm. J. Geophys. Res., 113, D24206, doi:10.1029/2008JD010832.
  109. Vukicevic, T., and D. J. Posselt 2008: Analysis of the Impact of Model Nonlinearities in Inverse Problem Solving. J. Atmos. Sci., 65, 2803-2823.
  110. Otkin, J. A., D. J. Posselt, E. R. Olson, H.-L. Huang, J. E. Davies, J. Li, and C. Velden, 2007: Mesoscale Numerical Weather Prediction Models Used in Support of Infrared Hyperspectral Measurements Simulation and Product Algorithm Development. J. Atm. Ocn. Tech., 24, 585-601.
  111. Posselt, D. J., and J. E. Martin, 2004: The Effect of Latent Heat Release on the Evolution of a Warm Occluded Thermal Structure., Mon. Wea. Rev., 132, 578-599.
  112. Huang, H.-L., D. C. Tobin, J. Li, E. R. Olson, K. Baggett, B. Huang, J. Mecikalski, R. O. Knuteson, B. Osborne, D. Posselt, P. B. Antonelli, H. E. Revercomb, W. L. Smith, and P. Yang, 2003: Hyperspectral radiance simulator: cloudy radiance modeling and beyond., Proc. SPIE 4891, 180 (2003), DOI:10.1117/12.466054