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PSU WRF EnKF Code Release Page


INTRODUCTION

The PSU EnKF system was led and developed by Fuqing Zhang and Yonghui Weng with contributions from past and current graduate students that include Zhiyong Meng (now at Peking University), Altug Aksoy (now at NOAA/HRD), Jonathan Poterjoy (now at NCAR/ASP), Jason Sippel (now at NOAA/EMC and IMSG), Meng Zhang (now at IBM Global Research), Christopher Melhauser (current) and Michael Ying (current), among many others. We acknowledge the funding support from NSF, ONR, NOAA and NASA for the research and development of this system over the past decade.


TERMS OF USE

IMPORTANT! READ BEFORE DOWNLOAD!

This message is sent on behalf of the code developers and is intended for PSU WRF EnKF code users. The code is free for use at user’s own risk. PSU ADAPT center makes no claim, promise, or guarantee about the completion of the code. We will respond to queries if we have time but no guarantee all questions can be answered. We do not answer computer platform related questions. The users of PSU WRF EnKF code are required to acknowledge in their published studies with citation to the papers listed below: Zhang et al. (2006), Meng and Zhang (2007, 2008a,b), Zhang et al. (2009, 2011), Weng and Zhang (2012).


REFERENCES

  1. Zhang, F., Z. Meng*, and A. Aksoy*, 2006: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part I: Perfect model experiments. Monthly Weather Review, 134, 722-736.
  2. Meng, Z.*, and F. Zhang, 2007: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part II: Imperfect model experiments. Monthly Weather Review, 135, 1403-1423 
  3. Meng, Z.*, and F. Zhang, 2008a: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part III: Comparison with 3DVAR in a real-data case study. Monthly Weather Review, 136, 522-540.
  4. Meng, Z.*, and F. Zhang, 2008b: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part IV: Comparison with 3DVAR in a month-long experiment. Monthly Weather Review, 136, 3671-3682.
  5. Zhang, F., Y. Weng*, J. A. Sippel, Z. Meng, and C. H. Bishop, 2009: Cloud-resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter. Monthly Weather Review, 137, 2105-2125.
  6. Zhang, F., Y. Weng*, J. F. Gamache, and F. D. Marks, 2011: Performance of Convection-permitting Hurricane Initialization and Prediction during 2008-2010 with Ensemble Data Assimilation of Inner-core Airborne Doppler Radar ObservationsGeophysical Research Letters38, L15810, doi:10.1029/2011GL048469.
  7. Weng, Y.*, and F. Zhang, 2012: Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-permitting Hurricane Initialization and Prediction: Katrina (2005). Monthly Weather Review140, 841-859.

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PSU WRF/EnKF Real-time Atlantic Hurricane Forecast System


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